Professor Stephan Chalup
Professor
School of Information and Physical Sciences (Data Science and Statistics)
- Email:stephan.chalup@newcastle.edu.au
- Phone:(02) 492 16080
Computers that ‘think’ like humans
By studying how the human mind works, Professor Stephan Chalup and his research team are developing clever machines that mimic the way we learn.
Professor Stephan Chalup and his research team at the University of Newcastle are contributing to an entirely new generation of machine learning. Using artificial neural networks—a machine learning tool inspired by the human brain—they have developed a suite of robots and computer systems that replicate the way human minds learn, process information and complete tasks.
“In my lab, we use what is known about how the mind works—how the neurons in the brain interact—to develop computer programs that allow machines to analyse images, sound recordings or process other data.”
Our human minds are constantly scanning the environment, processing huge amounts of information and deciding how to respond. For example, what happens when we walk into a café with a friend and have to decide where to sit? Our senses immediately kick in, studying the environment and available tables, what we know about our friend and about our own preferences. Our brain processes all the information we need to make a decision that may seem trivial to us but is very hard to implement realistically on a companion robot.
“By investigating these abstract underlying principles of the human neural systems, we can create artificial neural network simulations that can perform pattern analysis and control tasks.”
Stephan’s work has revealed new possibilities across the fields of artificial intelligence, machine learning, pattern recognition, data analysis, computer vision and control. It also presents exciting opportunities for industries. From solving complex challenges such as new methods in the minerals and mining industry, transport safety, through to deep data analysis needed for medical breakthroughs, the applications of Stephan’s work are extensive.
“After all these years, it is still amazing to see what artificial neural networks can do.”
A new generation of smart robots
Stephan and his team have recently developed new artificial neural networks for robots that allow them to detect objects more accurately and with higher frame rates than ever thought possible. His robots can perform complex tasks, and Stephan enjoys putting them to the test—and showing off their abilities.
“Our robot soccer team, the NUbots, has won two world titles. If you think about it, soccer is a highly complex task for a robot to perform. Our team of researchers and students have travelled to many cities around the world to participate in RoboCup, and our work has inspired an increasing number of young people to become involved in robotics.”
“It is fun to work in the lab with my team, students and colleagues. It’s satisfying work, and we’re proud to contribute to Australia’s international reputation in this field.”
The students that Stephan mentors are always excited to be involved in new projects happening at the lab. Their hands-on experience also stands them in good stead for a successful career, developing and testing the next generation of robotics and computer technology.
“Our robotics lab has some of the best computers and robots, as well as a team of very talented and motivated students. Alumni from our lab now work in some of the most fascinating jobs around the world.”
Practical industry solutions
Along with tearing up the soccer field, Stephan’s computer systems are also helping to solve complex industry challenges across the Hunter and worldwide. Stephan’s interdisciplinary research has led to advancements in medical imaging, architectural design analysis, material science and transport safety—just to name a few.
“We have used our experience with artificial neural networks and deep learning to improve train transport safety for local industry. Our machines can detect objects and dangerous situations along the track faster and with higher precision than previously thought possible.”
“Other areas of our work could be used in medical imaging to improve health. We have been implementing machine learning methods on robots that could be useful, for example, within the independent living domain as care robots.”
To achieve the best outcomes, Stephan’s work is often conducted in partnership with other disciplinary teams at the University of Newcastle. This interdisciplinary approach to research allows his work to be applied in novel ways.
“I enjoy interdisciplinary research and new challenges. For example, over about eight years I collaborated with a colleague in architecture on two Australian Research Council (ARC) Discovery Projects. Some of the work we did inspired researchers on the other side of the globe to do related work based on our projects.”
Understanding high-dimensional data
Stephan’s most recent work has included studies on high-dimensional data. Before computer systems can solve a problem, they must sort through and categorise an enormous amount of data with extensive numbers of variables. Traditionally, mathematical techniques have enabled machines to predict the future based on past data. Stephan and his team have posed a different idea.
“We found that some of our new techniques based on neural network principles work more robustly and more efficiently in applications than traditional deterministic methods.”
“In some recent work we learned how employ neural networks and algebraic topology to analyse and better understand 3D or high-dimensional data.”
The power of the human mind
Stephan’s work is built on an in-depth understanding of the human brain and how it works as a complex and powerful processing system. Yet Stephan explains that our biological neural networks are still “grossly underestimated”.
Through his work, Stephan aims to explain how human thoughts are represented and processed in our brains—and provide tantalising insights into what makes us tick.
“We want to provide humans with a better understanding of their own abilities and limitations, not so that artificial intelligence becomes more powerful and gains control, but so that us humans can deal with the world in a better way.”
Computers that ‘think’ like humans
By studying how the human mind works, Professor Stephan Chalup and his research team are developing clever machines that mimic the way we learn.Professor Stephan Chalup and his research team at the University of Newcastle are contributing to an entirely…
Career Summary
Biography
Professor Stephan Chalup conducts research in the field of Artificial Intelligence and Machine Learning. He received his Ph.D. in Computing Science in 2002 from Queensland University of Technology in Brisbane, where he studied at the Machine Learning Research Centre. Before he came to Australia, he completed postgraduate studies at the Master's level in mathematics with neuroscience at the University of Heidelberg and pursued undergraduate studies at the University of Konstanz.
Currently serving as the chief investigator of the ARC Discovery Project titled "Estimating the Topology of Low-Dimensional Data Using Deep Neural Networks," Stephan envisions the development of experimental software tools that empower individuals with the ability to intuitively understand complex 3-dimensional and 4-dimensional data that was previously beyond the limits of human visual comprehension [1].
As the head of the Interdisciplinary Machine Learning Research Group (IMLRG), Stephan directs one of Newcastle’s longest-running research groups. Collaborating with students, colleagues, and industry partners from diverse disciplines such as transport, fine art, electrical engineering, radiation therapy, mental health nursing, rock and coal science, and environmental biology, he has applied his expertise across various domains. A notable outcome of his long-term collaboration with the field of architecture is the introduction of a novel design evaluation approach that leverages the concept of facial pareidolia, enabling the detection of face-like patterns in house facades and random structures [2].
Stephan is also the director of the Newcastle Robotics lab, which is home to the renowned NUbots, a robot soccer team that achieved world champion titles at RoboCup in 2006 and 2008. The NUbots have not only captivated the public’s interest but have also inspired countless students across all age groups. The lab’s research outputs address advancements in software for low-powered devices, including the development of one of the world’s fastest computer vision systems [3].
Stephan’s passion for artificial intelligence and machine learning traces back more than two decades when he implemented a neural network simulator and demonstrated that a small recurrent neural network can be trained to predict symbol sequences of a context-sensitive language, which exhibits a level of formal complexity comparable to natural language [4]. This pioneering research can be regarded as an early precursor to current advancements in large language models.
References
[1] Khalil Mathieu Hannouch and Stephan Chalup (2023). Learning to See Topological Properties in 4D Using Convolutional Neural Networks. In 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML) at ICML 2023. PMLR.
[2] Asad Abbas and Stephan Chalup (2019).From Face Recognition to Facial Pareidolia: Analysing Hidden Neuron Activations in CNNs for Cross-Depiction Recognition. 2019 International Joint Conference on Neural Networks (IJCNN 2019), IEEE.
[3] Trent Houliston and Stephan K. Chalup (2018) Visual Mesh: Real-Time Object Detection Using Constant Sample Density. RoboCup 2018: Robot World Cup XIX, Lecture Notes in Artificial Intelligence (LNAI). Springer International Publishing, Cham. arXiv:1807.08405.
[4] Stephan K. Chalup and Alan D. Blair (2003). Incremental Training of First Order Recurrent Neural Networks to Predict a Context-Sensitive Language. Neural Networks 16(7), pp. 995-972.
Qualifications
- PhD, Queensland University of Technology
- Diplom in Mathematiker (equiv Degree), University of Heidelberg
Keywords
- Affective Computing
- Artificial Intelligence
- Artificial Neural Networks
- Autonomous Robots
- Big Data Analytics
- Biocybernetics
- Brain Science
- Computer Vision
- Cybernetics
- Data Science
- Deep Learning
- Deep Neural Networks
- Dimensionality Reduction
- Machine Learning
- Manifold Learning
- Neural Information Processing
- Pattern Recognition
- Signal Processing
- Support Vector Machines
- Topological Data Analysis
Languages
- English (Fluent)
- German (Fluent)
Fields of Research
Code | Description | Percentage |
---|---|---|
461105 | Reinforcement learning | 30 |
461103 | Deep learning | 60 |
460202 | Autonomous agents and multiagent systems | 10 |
Professional Experience
UON Appointment
Title | Organisation / Department |
---|---|
Professor | University of Newcastle School of Electrical Engineering and Computing Australia |
Professional appointment
Dates | Title | Organisation / Department |
---|---|---|
1/1/2019 - 31/12/2019 | Conference Local Chair and Program Co-chair | The 23rd Annual RoboCup International Symposium 2019 Australia |
1/1/2014 - 28/2/2015 |
Conference General Chair ACALCI 2015 |
Australasian Conference on Artificial Life and Computational Intelligence 2015 (ACALCI 2015) Australia |
Awards
Award
Year | Award |
---|---|
2008 |
RoboCup World Champion, China RoboCup Federation |
2006 |
RoboCup World Champion, Germany RoboCup Federation |
Research Award
Year | Award |
---|---|
2019 |
Best Student Paper Award (SocProS 2019) International Conference on Soft Computing for Problem Solving |
2018 |
Best Student Paper Award (BIBE 2018) The 18th annual IEEE International Conference on Bioinformatics and Bioengineering (BIBE 2018) |
2015 |
Faculty of Engineering and Built Environment Award for Supervision Research Excellence Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
2011 |
Best Student Paper Award (ANZAScA) The 45th Annual Conference of the Australian and New Zealand Architectural Science Association (ANZAScA) |
2005 |
Best paper award at IADIS International Conference IADIS International Conference e-Commerce |
2004 |
Engineering Challenge Paper Award RoboCup Federation |
Invitations
Committee Member
Year | Title / Rationale |
---|---|
2023 | International Joint Conference on Neural Networks (IJCNN 2023) |
2023 | 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML) at ICML 2023 |
2021 | The 34th Australasian Joint Conference on Artificial Intelligence |
2021 | International Conference on Deep Learning Theory and Applications (DeLTA 2021) |
2019 | The 32nd Australasian Joint Conference on Artificial Intelligence (AI 2019) |
2019 | European Conference on Mobile Robots (ECMR) |
2019 | 28th International Conference on Artificial Neural Networks (ICANN19) |
2018 | 22nd International RoboCup Symposium 2018 |
2018 | Automining 2018 - 6th International Congress on Automation in Mining |
2018 |
9th Annual International Conference on Computer Science Education: Innovation and Technology (CSEIT 2018) Program committee |
2017 | 21st Annual RoboCup International Symposium 2017 |
2017 | 8th Annual International Conference on Computer Science Education: Innovation & Technology (CSEIT 2017 ) |
Keynote Speaker
Year | Title / Rationale |
---|---|
2023 |
The 1 2 3 of PhD SIPS HDR Research Symposium, University of Newcastle |
2019 |
Robot Brains and the Development of Artificial Intelligence in Robot Soccer |
2017 |
Opportunities in Big Data Seminar/Webinar for Engineers Australia |
2016 |
Computing in the Robotics Lab to Increase STEM Interests from Primary School to PhD Levels of Education International Conference on Computer Science Education: Innovation and Technology (CSEIT 2016) |
2006 |
Approaching Complex Tasks with Kernel Methods Information Management and Market Engineering Workshop, Karlsruhe Institute of Technology (KIT), Germany |
Speaker
Year | Title / Rationale |
---|---|
2023 |
Aspects of Artificial Brain Science Hunter Medical Research Institute (HMRI), Brain Modulation Research Program, Annual Symposium |
2022 |
Vision and Visualisation Using Deep Learning Mathematical Thinking Workshop, Priority Research Centre for Computer-Assisted Research Mathematics and its Applications (CARMA), The University of Newcastle |
2018 |
Artificial Neural Networks - Old and New AMSI Research, CARMA Special Semester on Computation and Visualisation |
2018 |
Towards Combinations of Deep Networks Northern Lights Deep Learning Workshop 2018 |
2017 |
From Interdisciplinary Machine Learning to Brain Architecture Priority Research Centre for Computer Assisted Research-Mathematics and its Applications |
2012 |
Artificial Pedestrians for Analysing Perception of Urban Space Kolloquium Angewandte Informatik, Karlsruhe Institute of Technology (KIT), Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB) |
2012 |
Simulating Mechanisms of Emotion Associated with Visual Perception of Urban Space: An Artificial Agents Perspective Salk Institute for Biological Sciences, La Jolla, USA |
2009 |
New Computational Approaches to Architectural Image Analysis Karlsruhe Institute of Technology (KIT), Germany |
2008 |
Nature Inspired Computing Meets the Real World Engineers Australia (IEAust). Williamtown, Australia |
2008 |
Overview of the Newcastle Robotics Lab Robotics Institute of Harbin Institute of Technology (HIT) |
2008 |
Robotik, Sprachverarbeitung und Musik Hochschule fur Musik, Karlsruhe |
2004 |
To See or Not to Be in the Four-Legged League Department of Brain and Cognitive Sciences at The Massachusetts Institute of Technology (MIT), Cambridge, MA, USA |
Teaching
Code | Course | Role | Duration |
---|---|---|---|
COMP3330 |
Machine Intelligence Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
Course Coordinator | 26/2/2018 - 27/7/2022 |
COMP3320 |
Computer Graphics Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
Course Coordinator | 1/7/2018 - 20/12/2019 |
STAT2000 |
Applied Statistics and Research Methods School of Information and Physical Sciences, The University of Newcastle, Australia |
Lecturer | 21/2/2023 - 14/3/2023 |
COMP4130 |
Special Topic C: Advances in Deep Learning Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
Course Coordinator | 26/2/2018 - 27/7/2018 |
COMP6380 |
Machine Intelligence University of Newcastle |
Course Coordinator | 26/2/2018 - 27/7/2020 |
COMP3320/6370 |
Computer Graphics School of Information and Physical Sciences, The University of Newcastle, Australia |
Course coordinator | 1/7/2021 - 16/12/2022 |
COMP6003 |
Big Data Analytics University of Newcastle |
Course Coordinator | 4/9/2017 - 15/12/2017 |
STAT1060 |
Business Decision Making School of Information and Physical Sciences, The University of Newcastle, Australia |
Course Coordinator | 1/7/2022 - 16/12/2022 |
COMP4130 |
Special Topic C: Deep Learning and Neural Systems – Theory and Applications The University of Newcastle, Faculty of Engineering and built Environment, School of Electrical Engineering and Computing |
Course Coordinator | 26/2/2019 - 27/7/2019 |
COMP4110 |
Special Topic A: Computer Vision and Deep Learning The University of Newcastle |
Course Coordinator | 1/7/2017 - 15/12/2017 |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Highlighted Publications
Year | Citation | Altmetrics | Link | ||||||||
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2002 |
Yang J, Estivill-Castro V, Chalup SK, 'Support Vector Clustering Through Proximity Graph Modelling', 9th International Conference on Neural Information Processing, Singapore (2002) [E1]
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2003 |
Chalup SK, Blair AD, 'Incremental training of first order recurrent neural networks to predict a context-sensitive language', Neural Networks, 16 955-972 (2003) [C1]
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2017 |
Paul R, Chalup SK, 'A Study on Validating Non-Linear Dimensionality Reduction using Persistent Homology', Pattern Recognition Letters, 100 160-166 (2017) [C1]
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2019 |
Aziz F, Wong ASW, Chalup S, 'Semi-Supervised Manifold Alignment Using Parallel Deep Autoencoders', Algorithms, 12 186-186 (2019) [C1]
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2019 |
Paul R, Chalup S, 'Estimating Betti numbers using deep learning', 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary (2019) [E1]
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2023 |
Hannouch KM, Chalup S, 'Learning to See Topological Properties in 4D Using Convolutional Neural Networks', Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221, https://proceedings.mlr.press/v221/hannouch23a.html, Honolulu (2023)
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2024 |
Muller M, Kroon S, Chalup S, 'Topological Dynamics of Functional Neural Network Graphs During Reinforcement Learning', Neural Information Processing. 30th International Conference, ICONIP 2023, Changsha, China (2024) [E1]
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Book (1 outputs)
Year | Citation | Altmetrics | Link | ||
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2015 |
Chalup S, Blair A, Randall M, Artificial Life and Computational Intelligence: First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015. Proceedings, Springer International Publishing, Cham, 448 (2015) [A3]
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Chapter (6 outputs)
Year | Citation | Altmetrics | Link | ||||||||
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2020 |
Bakhshi A, Chalup S, Noman N, 'Fast Evolution of CNN Architecture for Image Classification', Deep Neural Evolution. Deep Learning with Evolutionary Computation, Springer, Singapore 209-229 (2020) [B1]
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2019 |
Aziz MFB, Chalup SK, Juniper J, 'Big Data in IoT Systems', Internet of Things (IoT): Systems and Applications, Jenny Stanford Publishing, Singapore 25-63 (2019) [B1]
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2019 |
Chiong R, Hu Z, Fan Z, Lin Y, Chalup S, Desmet A, 'A bio-inspired clustering model for anomaly detection in the mining industry', Bio-inspired Computing Models and Applications, World Scientific Publishing, Singapore 133-155 (2019) [B1]
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2010 |
Chalup SK, Ostwald M, 'Anthropocentric biocybernetic approaches to architectural analysis: New methods for investigating the built environment', Built Environment: Design Management and Applications, Nova Science Publishers, Hauppauge 121-145 (2010) [B1]
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2008 |
Chalup SK, Mitschele A, 'Kernel methods in finance', Handbook on Information Technology in Finance, Springer, Berlin 655-687 (2008) [B1]
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Show 3 more chapters |
Journal article (49 outputs)
Year | Citation | Altmetrics | Link | ||||||||
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2024 |
Shahab MB, Johnson SJ, Chalup S, 'Data-Driven Low-Complexity Detection in Grant-Free NOMA for IoT', IEEE Internet of Things Journal, 11 12388-12407 (2024)
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2023 |
Higgins O, Short BL, Chalup SK, Wilson RL, 'Artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health: An integrative review.', Int J Ment Health Nurs, 32 966-978 (2023) [C1]
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2023 |
Bretas AMC, Mendes A, Jackson M, Clement R, Sanhueza C, Chalup S, 'A decentralised multi-agent system for rail freight traffic management', ANNALS OF OPERATIONS RESEARCH, 320 631-661 (2023) [C1]
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2023 |
Higgins O, Short BL, Chalup SK, Wilson RL, 'Interpretations of Innovation: The Role of Technology in Explanation Seeking Related to Psychosis', PERSPECTIVES IN PSYCHIATRIC CARE, 2023 (2023) [C1]
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2023 |
Nesbitt K, Aziz F, Mahoney M, Chalup S, Lamichhane BP, 'Classifying coke using CT scans and landmark multidimensional scaling', INTERNATIONAL JOURNAL OF COAL SCIENCE & TECHNOLOGY, 10 (2023) [C1]
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2023 |
Rogers B, Noman N, Chalup S, Moscato P, 'A comparative analysis of deep neural network architectures for sentence classification using genetic algorithm', Evolutionary Intelligence, (2023) [C1] Because of the number of different architectures, numerous settings of their hyper-parameters and disparity among their sizes, it is difficult to equitably compare various deep ne... [more] Because of the number of different architectures, numerous settings of their hyper-parameters and disparity among their sizes, it is difficult to equitably compare various deep neural network (DNN) architectures for sentence classification. Evolutionary algorithms are emerging as a popular method for the automatic selection of architectures and hyperparameters for DNNs whose generalisation performance is heavily impacted by such settings. Most of the work in this area is done in the image domain, leaving text analysis, another prominent application domain of deep learning, largely absent. Besides, literature presents conflicting claims regarding the superiority of one DNN architecture over others in the context of sentence classification. To address this issue, we propose a genetic algorithm (GA) for optimising the architectural and hyperparameter settings in different DNN types for sentence classification. To enable the representation of the wide variety of architectures and hyperparameters utilised in DNNs, we employed a generalised and flexible encoding scheme in our GA. Our study involves optimising two convolutional and three recurrent architectures to ensure a fair and unbiased evaluation of their performance. Furthermore, we explore the effects of using F1 score versus accuracy as a performance metric during evolutionary optimisation of those architectures. Our results, using ten datasets, show that, in general, the architectures and hyperparameters evolved using the F1 score tended to outperform those evolved using accuracy and in the case of CNN and BiLSTM the results were significant in statistical measures. Of the five architectures considered, the GA-evolved gated recurrent unit (GRU) performed the strongest overall, achieving good generalisation performance while using relatively few trainable parameters, establishing GRU as the preferred architecture for the sentence classification task. The optimised architectures exhibited comparable performance with the state-of-the-art, given the large difference in trainable parameters.
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2023 |
Bretas AMC, Mendes A, Chalup S, Jackson M, Clement R, Sanhueza C, 'Addressing deadlock in large-scale, complex rail networks via multi-agent deep reinforcement learning', Expert Systems, [C1]
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2022 |
Bakhshi A, Harimi A, Chalup S, 'CyTex: Transforming speech to textured images for speech emotion recognition', SPEECH COMMUNICATION, 139 62-75 (2022) [C1]
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2022 |
Choi JH, Asadi B, Simpson J, Dowling JA, Chalup S, Welsh J, Greer P, 'Investigation of a water equivalent depth method for dosimetric accuracy evaluation of synthetic CT', PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 105 (2022) [C1]
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2022 |
Hayward MW, Chalup S, Khan J, Callen A, Klop-Toker K, Griffin A, 'A call to scale up biodiversity monitoring from idiosyncratic, small-scale programmes to coordinated, comprehensive and continuous monitoring across large scales', Australian Zoologist, 42 514-533 (2022) [C1] Conservation managers cannot manage what they don't know about, yet our existing biodiversity monitoring is idiosyncratic and small in scale. One of Australia's commitme... [more] Conservation managers cannot manage what they don't know about, yet our existing biodiversity monitoring is idiosyncratic and small in scale. One of Australia's commitments to the Convention for Biological Diversity in 2015 was the creation of a national biodiversity monitoring programme. This has not yet occurred despite the urgent need to monitor common and threatened species, as highlighted by the challenges of determining the biodiversity impacts of the Black Summer fires of 2019/20. In light of improvements to automation, miniaturisation and powering devices, the world urgently needs to scale-up biodiversity monitoring to become coordinated, comprehensive and continuous across large scales. We propose the BIOMON project that could achieve this where individual sensor nodes use machine learning models to identify biodiversity via sound or photos onboard. This could be coupled with abiotic data on temperature and humidity, plus factors such as bushfire smoke. Nodes would be set within networks that transmit the results back to a central cloud repository where robust analyses are conducted and provided free to the public (along with the raw data). Network arrays could be set up across entire continents to measure the change in biodiversity. No one has achieved this yet, and significant challenges remain associated with training the algorithms, low power cellular network coverage, sensor power versus memory trade-offs, and sensor network placement. Much work is still needed to achieve these goals; however we are living in the 21st Century and such lofty goals cannot be achieved unless we start working towards them.
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2021 |
Abbas A, Chalup S, 'Affective analysis of visual scenes using face pareidolia and scene-context', Neurocomputing, 437 72-83 (2021) [C1] This study presents a new computer vision approach to perform affective analysis of a scene or object. The approach utilises a simulation of the phenomenon of face pareidolia that... [more] This study presents a new computer vision approach to perform affective analysis of a scene or object. The approach utilises a simulation of the phenomenon of face pareidolia that can be described as the perception of non-existent faces, for example, in random textures, clouds or rock formations. The emergence of face pareidolia in product designs and natural scenes can modulate affective perception of our everyday experiences without our conscious awareness. We propose a new deep learning method to simulate the face pareidolia ability of humans and predict associated emotional responses in two-dimensional valence and arousal space. Starting from a face detector that was trained on images of human faces, we propose a novel cross-domain weakly supervised three-step progressive domain adaptation approach to simulate face pareidolia by fine-tuning the human face detector on three types of synthetically generated sample images. Our approach fuses two deep network models, one model for predicting valence and arousal from abstract and minimal face-like patterns producing face pareidolia, and a second for recognising overall moods and context associated with the scene. To evaluate our approach, we constructed a new dataset containing instance-level annotations of face pareidolia occurrences as well as valence and arousal emotional values associated with the overall scene. The quantitative and qualitative experimental results of the present study demonstrate that our approach can outperform other state-of-the-art methods in face pareidolia detection as well as in predicting associated emotions.
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2020 |
Bakhshi A, Chalup S, Harimi A, Mirhassani SM, 'Recognition of emotion from speech using evolutionary cepstral coefficients', Multimedia Tools and Applications, 79 35739-35759 (2020) [C1]
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2020 |
Astono IP, Welsh JS, Chalup S, Greer P, 'Optimisation of 2D U-Net Model Components for Automatic Prostate Segmentation on MRI', Applied Sciences, 10 (2020) [C1]
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2020 |
Khan MM, Mendes A, Chalup SK, 'Performance of evolutionary wavelet neural networks in acrobot control tasks', Neural Computing and Applications, 32 8493-8505 (2020) [C1]
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2020 |
Gholizadeh N, Simpson J, Ramadan S, Denham J, Lau P, Siddique S, et al., 'Voxel-based supervised machine learning of peripheral zone prostate cancer using noncontrast multiparametric MRI', Journal of Applied Clinical Medical Physics, 21 179-191 (2020) [C1]
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2019 |
Mirjalili SZ, Mirjalili S, Zhang H, Chalup S, Noman N, 'Improving the reliability of implicit averaging methods using new conditional operators for robust optimization', Swarm and Evolutionary Computation, 51 (2019) [C1]
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2019 |
Liu J, Chen W, Muller M, Chalup S, Wheeler C, 'An automatic HyLogger mineral mapping method using a machine-learning-based computer vision technique', Australian Journal of Earth Sciences, 66 1063-1073 (2019) [C1]
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2019 |
Choi JH, Lee D, O'Connor L, Chalup S, Welsh JS, Dowling J, Greer PB, 'Bulk Anatomical Density Based Dose Calculation for Patient-Specific Quality Assurance of MRI-Only Prostate Radiotherapy', Frontiers in Oncology, 9 (2019) [C1]
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2019 |
Aziz F, Wong ASW, Chalup S, 'Semi-Supervised Manifold Alignment Using Parallel Deep Autoencoders', Algorithms, 12 186-186 (2019) [C1]
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2018 |
Khan MM, Mendes A, Chalup SK, 'Evolutionary wavelet neural network ensembles for breast cancer and Parkinson s disease prediction', PLoS ONE, 13 (2018) [C1]
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2018 |
Ma M, Cheng D, Chalup S, Zhou Z, 'Uncertainty Estimation in the Neural Model for Aeromagnetic Compensation', IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 15 1942-1946 (2018) [C1]
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2017 |
Khan MM, Mendes A, Zhang P, Chalup SK, 'Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming', NEUROCOMPUTING, 247 39-58 (2017) [C1]
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2017 |
Paul R, Chalup SK, 'A Study on Validating Non-Linear Dimensionality Reduction using Persistent Homology', Pattern Recognition Letters, 100 160-166 (2017) [C1]
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2016 |
Abed-Alguni B, Paul D, Chalup S, Henskens FA, 'A Comparison Study of Cooperative Q-learning Algorithms for Independent Learners', International Journal of Artificial Intelligence, 14 71-93 (2016) [C1]
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2016 |
Houliston T, Fountain J, Lin Y, Mendes A, Metcalfe M, Walker J, Chalup SK, 'NUClear: A Loosely Coupled Software Architecture for Humanoid Robot Systems', Frontiers in Robotics and AI, 3 1-15 (2016) [C1]
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2015 |
Abed-alguni BH, Chalup SK, Henskens FA, Paul DJ, 'A multi-agent cooperative reinforcement learning model using a hierarchy of consultants, tutors and workers', Vietnam Journal of Computer Science, 2 213-226 (2015) [C1]
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2014 |
Hong K, Chalup SK, King RAR, 'Affective visual perception using machine pareidolia of facial expressions', IEEE Transactions on Affective Computing, 5 352-363 (2014) [C1] This article presents a computer vision approach that can detect and classify abstract face-like patterns, including subliminal faces within a scene. This can be regarded as a way... [more] This article presents a computer vision approach that can detect and classify abstract face-like patterns, including subliminal faces within a scene. This can be regarded as a way of simulating the phenomenon of pareidolia, that is, the tendency of humans to 'see faces' in random structures such as clouds or rocks. The paper describes the system consisting of a component-based face detector and an expression classifier. The face detector creates a number of component images from the original image at different resolutions. A component image is a binary edge image where the edges are segmented into components using a labelling method with a border-following technique. The component images are then overlaid to produce a component height map where large and notable components across all resolutions have high values, while specular and noisy components have low values. The method retains three-shape components, representing two eyes and a mouth, that have height map values that are larger than the noise cut-off value. Support vector machines using scale-invariant feature vectors are applied for ranking these three-shape components by their geometry and size, and their shape semblance to human faces in the training data. The outcome is a facial expression analysis system that uses face components, with the potential to estimate an emotional expression value for a scene by producing an array of emotion scores corresponding to Ekman's seven Universal Facial Expressions of Emotion. An advantage of this technique, when compared to a holistic method, is that the face components are explicitly isolated. This supports a process of abstraction that can facilitate the detection of distorted and minimal face-like patterns.
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2014 |
Boecking B, Chalup SK, Seese D, Wong ASW, 'Support vector clustering of time series data with alignment kernels', Pattern Recognition Letters, 45 129-135 (2014) [C1] Time series clustering is an important data mining topic and a challenging task due to the sequences' potentially very complex structures. In the present study we experimenta... [more] Time series clustering is an important data mining topic and a challenging task due to the sequences' potentially very complex structures. In the present study we experimentally investigate the combination of support vector clustering with a triangular alignment kernel by evaluating it on an artificial time series benchmark dataset. The experiments lead to meaningful segmentations of the data, thereby providing an example that clustering time series with specific kernels is possible without pre-processing of the data. We compare our approach and the results and learn that the clustering quality is competitive when compared to other approaches. © 2014 Published by Elsevier B.V.
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2013 |
Bhatia S, Chalup SK, Ostwald MJ, 'Wayfinding: A method for the empirical evaluation of structural saliency using 3D Isovists', Architectural Science Review, 56 220-231 (2013) [C1] The presence of locations that possess distinct spatial-cognitive features (salient landmarks) is a fundamental necessity for supporting navigation. Embedding formal or structural... [more] The presence of locations that possess distinct spatial-cognitive features (salient landmarks) is a fundamental necessity for supporting navigation. Embedding formal or structural variability sufficient to create such landmark locations is therefore an important consideration in the design of large urban and architectural spaces. Despite the availability of diverse theories that seek to identify the characteristics of a salient landmark, relatively few experimental techniques are available to empirically evaluate saliency in a given architecture plan. This study is therefore motivated by the development of an ability to measure spatial distinctiveness during the architectural design and modelling process. The information from such an analysis can prove useful for evaluating the way in which a design provides support for wayfinding and spatial appeal. Statistical summaries obtained from the three-dimensional (3D) isovists are compared using principal component analysis to differentiate monotonous regions from the more structurally distinct ones. The experiments reported in the paper demonstrate novel utilization of the isovist concept to capture spatial properties and comparison of structural saliency among two well-known architectural designs. Central contributions of the paper include the novel experimentation technique of capturing and utilizing 3D isovists, its interpretation and the quantitative methodology behind saliency computation. © 2013 Copyright Taylor and Francis Group, LLC.
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2013 |
Jalalian A, Chalup SK, 'GDTW-P-SVMs: Variable-length time series analysis using support vector machines', NEUROCOMPUTING, 99 270-282 (2013) [C1]
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2013 |
Bhatia S, Chalup SK, 'Segmenting Salient Objects in 3D Point Clouds of Indoor Scenes Using Geodesic Distances', Journal of Signal and Information Processing, 4 102-108 (2013) [C1]
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2012 |
Wong AS, Chalup SK, Bhatia S, Jalalian A, Kulk JA, Nicklin SP, Ostwald M, 'Visual gaze analysis of robotic pedestrians moving in urban space', Architectural Science Review, 55 213-223 (2012) [C1]
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2011 |
Jalalian A, Chalup SK, Ostwald M, 'Architectural evaluation of simulated pedestrian spatial behaviour', Architectural Science Review, 54 132-140 (2011) [C1]
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2010 | Chalup SK, Hong K, Ostwald M, 'Simulating pareidolia of faces for architectural image analysis', International Journal of Computer Information Systems and Industrial Management Applications, 2 262-278 (2010) [C1] | Nova | |||||||||
2009 |
Ostwald M, Vaughan JL, Chalup SK, 'A computational investigation into the fractal dimensions of the architecture of Kazuyo Sejima', Design Principles & Practices: An International Journal, 3 231-244 (2009) [C1]
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2009 | Chalup SK, Ostwald M, 'Anthropocentric biocybernetic computing for analysing the architectural design of house facades and cityscapes', Design Principles & Practices: An International Journal, 3 65-80 (2009) [C1] | Nova | |||||||||
2009 |
Chalup SK, Henderson N, Ostwald M, Wiklendt LS, 'A computational approach to fractal analysis of a cityscape's skyline', Architectural Science Review, 52 126-134 (2009) [C1]
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2009 |
Wiklendt LS, Chalup SK, Middleton RH, 'A small spiking neural network with LQR control applied to the acrobot', Neural Computing & Applications, 18 369-375 (2009) [C1]
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2009 |
Wiklendt LS, Chalup SK, Seron MM, 'Simulated 3D biped walking with an evolution-strategy tuned spiking neural network', Neural Network World, 19 235-246 (2009) [C1]
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2008 |
Goldsmith BE, Chalup SK, Quinlan MJ, 'Regime type and international conflict: Towards a general model', Journal of Peace Research, 45 743-763 (2008) [C1]
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2007 |
Chalup SK, Wiklendt LS, 'Variations of the two-spiral task', Connection Science, 19 183-199 (2007) [C1]
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2007 |
Chalup SK, Murch CL, Quinlan MJ, 'Machine learning with AIBO robots in the four-legged league of RoboCup', IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 37 297-310 (2007) [C1]
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2006 | Dietrich T, Seese D, Chalup SK, 'Classification of EBAY Bidding Characteristics', IADIS International Journal on WWW/Internet, 4 111-125 (2006) [C1] | ||||||||||
2005 |
Chalup SK, Mellor D, Rosamond FA, 'The Machine Intelligence Hex Project', Computer Science Education, 15 245-273 (2005) [C1]
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2005 | Young SR, Chalup SK, 'Towards robot soccer team behaviours through approximate simulation', 2005 4TH IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING, 162-162 (2005) | ||||||||||
2004 |
Middleton RH, Chalup SK, Quinlan MJ, Murch CL, 'Traction monitoring for collision detection with legged robots', Lecture Notes in Artificial Intelligence, 3020 374-384 (2004) [C1]
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2004 |
Chalup SK, Middleton RH, Quinlan MJ, Wiklendt LS, 'Neurocomputational aspects of legged locomotion motor control', Proceedings of the Australian Neuroscience Society, 15 105 (2004) [C3]
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2003 |
Chalup SK, Blair AD, 'Incremental training of first order recurrent neural networks to predict a context-sensitive language', Neural Networks, 16 955-972 (2003) [C1]
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2002 |
Chalup SK, 'Incremental Learning in Biological and Machine Learning Systems', International Journal of Neural Systems, 12 447-465 (2002) [C1]
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Show 46 more journal articles |
Conference (114 outputs)
Year | Citation | Altmetrics | Link | ||||||||
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2024 |
Muller M, Kroon S, Chalup S, 'Topological Dynamics of Functional Neural Network Graphs During Reinforcement Learning', Neural Information Processing. 30th International Conference, ICONIP 2023, Changsha, China (2024) [E1]
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2024 |
Biddulph A, Houliston T, Mendes A, Chalup S, 'Stereo Visual Mesh for Generating Sparse Semantic Maps at High Frame Rates', Lecture Notes in Computer Science (LNCS), vol 14452, Changsha, China (2024) [E1]
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2023 |
Bakhshi A, García-Gómez J, Gil-Pita R, Chalup S, 'Violence Detection in Real-Life Audio Signals Using Lightweight Deep Neural Networks', Procedia Computer Science, Online (2023) [E1]
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2023 |
Peek D, Skerritt MP, Chalup S, 'Synthetic Data Generation and Deep Learning for the Topological Analysis of 3D Data', 2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023 (2023) This research uses deep learning to estimate the topology of manifolds represented by sparse, unordered point cloud scenes in 3D. A new labelled dataset was synthesised to train n... [more] This research uses deep learning to estimate the topology of manifolds represented by sparse, unordered point cloud scenes in 3D. A new labelled dataset was synthesised to train neural networks and evaluate their ability to estimate the genus of these manifolds. This data used random homeomorphic deformations to provoke the learning of visual topological features. We demonstrate that deep learning models could extract these features and discuss some advantages over existing topological data analysis tools that are based on persistent homology. Semantic segmentation was used to provide additional geometric information in conjunction with topological labels. Common point cloud multi-layer perceptron and transformer networks were both used to compare the viability of these methods. The experimental results of this pilot study support the hypothesis that, with the aid of sophisticated synthetic data generation, neural networks can perform segmentation-based topological data analysis. While our study focused on simulated data, the accuracy achieved suggests a potential for future applications using real data.
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2023 |
Hannouch KM, Chalup S, 'Learning to See Topological Properties in 4D Using Convolutional Neural Networks', Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221, https://proceedings.mlr.press/v221/hannouch23a.html, Honolulu (2023)
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2023 |
Sims Y, Mendes A, Chalup S, 'Enhanced Embeddings in Zero-Shot Learning for Environmental Audio', ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Rhodes Island, Greece (2023) [E1]
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2022 |
Rogers B, Noman N, Chalup S, Moscato P, 'Joint Optimization of Topology and Hyperparameters of Hybrid DNNs for Sentence Classification', 2022 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), ITALY, Padua (2022) [E1]
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2021 | Papasotiriou T, Chalup S, 'Global urban cityscape - Unsupervised clustering exploration of human activity and mobility infrastructure', Projections - Proceedings of the 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, CAADRIA 2021, Online (2021) [E1] | Nova | |||||||||
2021 |
Bakhshi A, Chalup S, 'Multimodal Emotion Recognition Based on Speech and Physiological Signals Using Deep Neural Networks', Pattern Recognition. ICPR International Workshops and Challenges, Virtual (2021) [E1]
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2021 |
Bretas AMC, Mendes A, Chalup S, Jackson M, Clement R, Sanhueza C, 'Freight train scheduling via decentralised multi-agent deep reinforcement learning', Proceedings of the International Congress on Modelling and Simulation, MODSIM (2021) Rail traffic planning and scheduling problems have been challenging academy and industry for a few decades. Specifically, problems in the short term and real-time horizons deal wi... [more] Rail traffic planning and scheduling problems have been challenging academy and industry for a few decades. Specifically, problems in the short term and real-time horizons deal with simultaneous decision-making of trains, stations and terminals. Approaches focused on decentralised decision-making have been successful in delivering real-world committed solutions. This work focuses on decentralised real-time decision-making in a closed freight rail network and applies multi-agent deep reinforcement learning (MADRL) to find efficient timetables. We apply the MADRL model to solve the traffic decisions arising in the Hunter Valley Coal Chain (HVCC) in New South Wales, Australia. The approach uses the same simulation model currently in use for capacity planning of the system, thus allowing tests with real data. The environment is modelled as a decentralised, partially observed Markov decision process (dec-POMDP), where the train, load point, and dump station agents decide upon train movements based on local observations. The observations follow a novel state encoding strategy for rail traffic management composed of nine layers. We benefit from this strategy to apply a decentralised execution with a centralised learning approach through proximal policy optimisation. The experiments revealed a significant performance improvement for the ten instances tested, which reproduce the challenges faced in the HVCC operations. The approach is suitable for varied levels of rail network complexity, generating efficient solutions without scaling issues. The MADRL outperformed the heuristic in use by HVCC's simulation model and a high-performance genetic algorithm in all instances, reaching performance improvements of up to 72.00% and 47.42%, respectively. Therefore, the framework with the MADRL and the simulation model allows its application with real world instances in an efficient and reliable way. These results show the method's consistency and draw a safe path towards a decentralised rail traffic management system.
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2021 |
Rogers B, Noman N, Chalup S, Moscato P, 'Evolutionary Hyperparameter Optimisation for Sentence Classification', 2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021), ELECTR NETWORK (2021) [E1]
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2021 |
Jalil SQ, Chalup S, Rehmani MH, 'Cognitive Radio Spectrum Sensing and Prediction Using Deep Reinforcement Learning', 2021 Proceedings of the International Joint Conference on Neural Networks, Shenzhen, China (2021) [E1]
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2020 |
Mirjalili S, Zhang H, Mirjalili S, Chalup S, Noman N, 'A Novel U-Shaped Transfer Function for Binary Particle Swarm Optimisation', Soft Computing for Problem Solving 2019. Proceedings of SocProS 2019, Liverpool, UK (2020) [E1]
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2020 |
Jalil SQ, Rehmani MH, Chalup S, 'A deep reinforcement learning approach to fair distributed dynamic spectrum access', ACM International Conference Proceeding Series, Online (2020) [E1]
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2020 |
Mirjalili SZ, Chalup S, Mirjalili S, Noman N, 'Robust Multi-Objective optimization using Conditional Pareto Optimal Dominance', 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings, Glasgow, UK (2020) [E1]
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2020 |
Bakhshi A, Wong ASW, Chalup S, 'End-to-end speech emotion recognition based on time and frequency information using deep neural networks', ECAI 2020 24th European Conference on Artificial Intelligence, Santiago de Compostela, Spain (2020) [E1]
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2020 |
Jalil SQ, Husain Rehmani M, Chalup S, 'DQR: Deep Q-Routing in Software Defined Networks', Proceedings of the 2020 International Joint Conference on Neural Networks, Glasgow, United Kingdom (2020) [E1]
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2020 |
Mobasher-Kashani M, Noman N, Chalup S, 'Parallel LSTM Architectures for Non-Intrusive Load Monitoring in Smart Homes', 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, Canberra, ACT (2020) [E1]
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2019 |
Abbas A, Chalup S, 'The Impact of Image Resolution on Facial Expression Analysis with CNNs', The 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary (2019) [E1]
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2019 |
Abbas A, Chalup S, 'From face recognition to facial pareidolia: Analysing hidden
neuron activations in cnns for cross-depiction recognition', 2019 International Joint Conference on Neural Networks (IJCNN 2019), Budapest, Hungary (2019) [E1]
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2019 |
Aziz F, Chalup S, 'Testing the robustness of manifold learning on examples of
thinned-out data', 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary (2019) [E1]
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2019 |
Bretas AMC, Mendes A, Jackson M, Clement R, Sanhueza C, Chalup S, 'A multi-agent system with reinforcement learning for railway traffic management', 13th International Conference on Bulk Materials Storage, Handling and Transportation ICBMH 2019, Surfers Paradise, Queensland (2019) [E1]
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2019 |
Jalil SQ, Chalup S, Rehmani MH, 'A Smart Meter Firmware Update Strategy Through Network Coding for AMI Network', Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Niagara Falls, ON (2019) [E1]
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2019 |
Bakhshi A, Noman N, Chen Z, Zamani M, Chalup S, 'Fast Automatic Optimisation of CNN Architectures for Image Classification Using Genetic Algorithm', 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, Wellington, NZ (2019) [E1]
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2019 |
Bretas A, Mendes A, Chalup S, Jackson M, Clement R, Sanhueza C, 'Modelling railway traffic management through multi-agent systems and reinforcement learning', MODSIM2019, 23rd International Congress on Modelling and Simulation, Canberra, Australia (2019) [E1]
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2019 |
Houliston T, Chalup SK, 'Visual Mesh: Real-Time Object Detection Using Constant Sample Density', RoboCup 2018: Robot World Cup XXII, Quebec, Canada (2019) [E1]
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2019 |
Jabbar A, Mendes A, Chalup S, 'Comparing Ellipse Detection and Deep Neural Networks for the Identification of Drinking Glasses in Images', Computer Vision Systems. 12th International Conference, ICVS 2019. Proceedings, Thessaloniki, Greece (2019) [E1]
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2019 |
Zahn B, Fountain J, Houliston T, Biddulph A, Chalup S, Mendes A, 'Optimization of Robot Movements Using Genetic Algorithms and Simulation', RoboCup 2019: Robot World Cup XXII, Sydney, Australia (2019) [E1]
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2019 |
Wong ASW, Jeffery R, Turner P, Sleap S, Chalup SK, 'RoboCup Junior in the Hunter Region: Driving the Future of Robotic STEM Education', RoboCup 2018: Robot World Cup XXII, Quebec, Canada (2019) [E1]
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2019 |
Paul R, Chalup S, 'Estimating Betti numbers using deep learning', 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary (2019) [E1]
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2018 |
Ginn D, Mendes A, Chalup S, Fountain J, 'Monocular ORB-SLAM on a humanoid robot for localization purposes', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Wellington, New Zealand (2018) [E1]
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2018 |
Biddulph A, Houliston T, Mendes A, Chalup SK, 'Comparing Computing Platforms for Deep Learning on a Humanoid Robot', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Siem Reap, Cambodia (2018) [E1]
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2018 |
Ginn D, Mendes A, Chalup S, Chen Z, 'Sliding Window Bag-of-Visual-Words for Low Computational Power Robotics Scene Matching', CONFERENCE PROCEEDINGS OF 2018 4TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND ROBOTICS (ICCAR), Auckland, NEW ZEALAND (2018) [E1]
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2018 |
Aziz F, Wong ASW, Welsh JS, Chalup SK, 'Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Siem Reap, Cambodia (2018) [E1]
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2018 |
Astono I, Welsh JS, Chalup S, 'Adjacent Network for Semantic Segmentation of Liver CT Scans', PROCEEDINGS 2018 IEEE 18TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE), TAIWAN, Taichung (2018) [E1]
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2017 |
Brankovic L, Chalup S, Wallis M, 'Teaching Advanced Computing Technologies to Managers, Engineers and Other Professionals', 28th Annual Conference of the Australasian Association for Engineering Education (AAEE 2017), Manly, Sydney (2017) [E1]
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2017 |
Abbas A, Chalup SK, 'Group Emotion Recognition in the Wild by Combining Deep Neural Networks for Facial Expression Classification and Scene Context Analysis', ICMI 17, Proceedings of the 19th ACM International Conference on Multimodal Interaction, Glasgow, Scotland (2017) [E1]
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2017 |
Jabbar A, Farrawell L, Fountain J, Chalup SK, 'Training Deep Neural Networks for Detecting Drinking Glasses using Synthetic Images', Neural Information Processing. 24th International Conference, ICONIP 2017, Guangzhou, China (2017) [E1]
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2017 |
Paul R, Bose RPJC, Chalup SK, Raravi G, 'Improving Operational Performance in Service Delivery Organizations by Using a Metaheuristic Task Allocation Algorithm', CEUR Workshop Proceedings: Proceedings of the BPM 2017 Industry Track, Barcelona, Spain (2017) [E1]
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2016 |
Bille RJ, Lin Y, Chalup SK, 'RTCSS: a framework for developing real-time peer-to-peer web applications', Proceeding ACSW '16 Proceedings of the Australasian Computer Science Week Multiconference, Canberra, Australia (2016) [E1]
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2016 |
Metcalfe M, Annable B, Olejniczak M, Chalup SK, 'A study on detecting three-dimensional balls using boosted classifiers', ACSW '16 Proceedings of the Australasian Computer Science Week Multiconference, Canberra, Australia (2016) [E1]
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2016 |
Khan MM, Chalup SK, Mendes A, 'Parkinson s disease data classification using evolvable wavelet neural networks', Artificial Life and Computational Intelligence. Second Australasian Conference, ACALCI 2016, Canberra, Australia (2016) [E1]
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2015 |
Fountain J, Chalup SK, 'Point of regard from eye velocity in stereoscopic virtual environments based on intersections of hypothesis surfaces', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2015) [E1] A new method is proposed for utilising scene information for stereo eye tracking in stereoscopic 3D virtual environments. The approach aims to improve gaze tracking accuracy and r... [more] A new method is proposed for utilising scene information for stereo eye tracking in stereoscopic 3D virtual environments. The approach aims to improve gaze tracking accuracy and reduce the required user engagement with eye tracking calibration procedures. The approach derives absolute Point of Regard (POR) from the angular velocity of the eyes without user engaged calibration of drift. The method involves reduction of a hypothesis set for the 3D POR via a process of transformation during saccades and intersection with scene geometry during fixations. A basic implementation of this concept has been demonstrated in simulation using the depth buffer of the scene and a particle representation for the hypothesis set. Future research directions will focus on optimisation of the algorithm and improved utilisation of scene information. The technique shows promise in improving gaze tracking techniques in general, including relative paradigms such as electrooculography.
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2015 | Fountain J, Chalup SK, 'Automatic Calibration of Eye Baseline In Virtual Environments Using Stereoscopic Set Transformation and Scene Intersection', Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015. Proceedings (2015) | ||||||||||
2015 |
Walker J, Chalup SK, 'Learning Nursery Rhymes using Adaptive Parameter Neurodynamic Programming', Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015. Proceedings, Newcastle, Australia (2015) [E1]
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2015 |
Houliston T, Metcalfe M, Chalup SK, 'A fast method for adapting lookup tables applied to changes in lighting colour', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2015) [E1] This paper proposes a simple and fast method for adapting colour lookup tables to lighting changes in real-time. The method adjusts the classified colour space regions keeping bot... [more] This paper proposes a simple and fast method for adapting colour lookup tables to lighting changes in real-time. The method adjusts the classified colour space regions keeping both their surface area and volume constant. Two variations of the method were compared and tested in a RoboCup soccer setting. Detection success rate was measured as a function of the speed and magnitude of hue change to the lighting environment. Compared to a static lookup table, these experimental results show improved robustness against lighting changes for detection of coloured objects.
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2014 |
Khan MM, Chalup SK, Mendes A, 'Evolving Wavelet Neural Networks for Breast Cancer Classification', Conferences in Research Practice and Information Technology, Brisbane, Qld (2014) [E1]
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2014 |
Fountain J, Walker J, Budden D, Mendes A, Chalup SK, 'Motivated reinforcement learning for improved head actuation of humanoid robots', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2014) [E1] The ability of an autonomous agent to self-localise within its environment is critically dependent on its ability to make accurate observations of static, salient features. This n... [more] The ability of an autonomous agent to self-localise within its environment is critically dependent on its ability to make accurate observations of static, salient features. This notion has driven considerable research into the development and improvement of feature extraction and object recognition algorithms, both within RoboCup and the robotics community at large. Instead, this paper focuses on the rarely-considered issue imposed by the limited field of view of humanoid robots; namely, determining an optimal policy for actuating a robot's head, to ensure it observes regions of the environment that will maximise the positional information provided. The complexity of this task is magnified by a number of common computational issues; specifically high dimensional state spaces and noisy environmental observations. This paper details the application of motivated reinforcement learning to partially overcome these issues, leading to an 11% improvement (relative to the null case of uniformly distributed actuation policies) in self-localisation and ball-localisation for an agent trained online for less than one hour. The method is demonstrated as a viable method for improving self-localisation in robotics, without the need for further optimisation of object recognition or tuning of probabilistic filters. © 2014 Springer-Verlag Berlin Heidelberg.
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2014 |
Khan M, Chalup S, Mendes A, 'Evolving wavelet neural networks for breast cancer classification', Conferences in Research and Practice in Information Technology Series (2014) Digital Mammograms are x-ray images of the breast and one of the preferred early detection methods for breast cancer. However, mammograms are still difficult to interpret, and ass... [more] Digital Mammograms are x-ray images of the breast and one of the preferred early detection methods for breast cancer. However, mammograms are still difficult to interpret, and associated with this problem is a high percentage of unnecessary biopsies, misdiagnoses and late detections. The focus of this research is to use neuroevolutionary mechanisms for detecting breast cancer from mammographic images. The aim is to design a sophisticated classification tool that detects breast cancer at its early stages, so that treatment has a better chance of success. Wavelet neural networks have the ability to capture and extract information at various frequency levels by using different dilation and scaling values of the wavelet function. In this work, the wavelet neural network parameters are evolved using on the concept of Cartesian Genetic Programming, resulting in an evolved neural network which is trained for mass diagnosis. In the reported study the proposed algorithm achieves a classification accuracy of 89.57% on a real dataset composed of 200 images. Such a computer- based classification system has the potential to provide a second opinion to the radiologists, thus assisting them to diagnose the malignancy of breast cancer more precisely.
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2014 |
Tan L, Bille R, Lin Y, Chalup SK, Tucker C, 'Software Development in the City Evolutions Project', Fun and Games: Proceedings of the 2014 Conference on Interactive Entertainment, Newcastle, NSW (2014) [E1]
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2013 |
Hong K, Chalup SK, King RAR, 'A component based approach for classifying the seven universal facial expressions of emotion', Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing, CICAC 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, Singapore (2013) [E1]
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2013 |
Hong K, Chalup SK, King RAR, Ostwald MJ, 'Scene Perception using Pareidolia of Faces and Expressions of Emotion', Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC), Singapore, SINGAPORE (2013) [E1]
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2013 |
Wong ASW, Nicklin S, Hong K, Chalup SK, Walla P, 'Robot emotions generated and modulated by visual features of the environment', IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC), Singapore, SINGAPORE (2013) [E1]
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2013 |
Chalup SK, Bhatia S, 'A model of heteroassociative memory: Deciphering surprising features and locations', Proceedings of the Fourth International Conference on Computational Creativity (ICCC 2013), Sydney (2013) [E1]
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2013 |
Budden D, Fenn S, Mendes A, Chalup S, 'Evaluation of colour models for computer vision using cluster validation techniques', Lecture Notes in Artificial Intelligence, Mexico City (2013) [E1]
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Nova | |||||||||
2012 | Chalup SK, Ostwald M, Walla PH, 'Simulating mechanisms of emotion associated with visual perception of urban space: An artificial agents perspective', Academy of Neuroscience for Architecture 2012 Annual Conference, La Jolla, CA (2012) [E3] | ||||||||||
2012 | Bhatia S, Chalup SK, Ostwald M, 'Analyzing architectural space: Identifying salient regions by computing 3D isovists', Conference Proceedings. 46th Annual Conference of the Architectural Science Association (ANZAScA), Gold Coast, QLD (2012) [E1] | ||||||||||
2012 |
Jalalian A, Chalup SK, Ostwald M, 'Analysis of pedestrian spatial behaviour using GDTW-P-SVMs', Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), Brisbane (2012) [E1]
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Nova | |||||||||
2012 |
Hong K, Chalup SK, King RA, 'An experimental evaluation of pairwise adaptive support vector machines', Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), Brisbane (2012) [E1]
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Nova | |||||||||
2011 |
Wong AS, Chalup SK, Bhatia S, Jalalian A, Kulk JA, Ostwald M, 'Humanoid robots for modelling and analysing visual gaze dynamics of pedestrians moving in urban space', Conference Proceedings 45th Annual Conference of the Australian and New Zealand Architectural Science Association, Sydney, NSW (2011) [E1]
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Nova | |||||||||
2011 |
Ostwald M, Vaughan JL, Chalup SK, 'Data flow and processing in the computational fractal analysis method', Proceedings of the 16th International Conference on Computer-Aided Architectural Design Research in Asia. CAADRIA 2011, Newcastle, NSW (2011) [E1]
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Nova | |||||||||
2011 |
Jalalian A, Chalup SK, Ostwald M, 'Agent-agent interaction as a component of agent-environment interaction in the modelling and analysis of pedestrian visual behaviour', Proceedings of the 16th International Conference on Computer-Aided Architectural Design Research in Asia. CAADRIA 2011, Newcastle, NSW (2011) [E1]
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Nova | |||||||||
2010 | Chalup SK, Ostwald M, 'Modelling architectural design perception using anthropocentric biocybernetic computing', Fourth International Conference On Design Computing And Cognition (DCC'10): Bringing Artificial Intelligence, Cognitive Science and Computational Theories to Design Research, Stuttgart, Germany (2010) [E3] | ||||||||||
2010 | Jalalian A, Chalup SK, Ostwald M, 'Evaluating urban streetscape design by analysing pedestrian body dynamics', Fourth International Conference On Design Computing And Cognition (DCC'10): Bringing Artificial Intelligence, Cognitive Science and Computational Theories to Design Research, Stuttgart, Germany (2010) [E3] | ||||||||||
2010 | Jalalian A, Chalup SK, Ostwald M, 'Simulating pedestrian flow dynamics for evaluating the design of urban and architectural space', On the Edge. Conference Papers of the 44th Annual Conference of ANZAScA, Auckland, NZ (2010) [E1] | Nova | |||||||||
2010 |
Jalalian A, Chalup SK, Ostwald M, 'Intelligent evaluation of urban streetscape designs by analysing pedestrian body dynamics', 3rd International Workshop on Advanced Computational Intelligence, IWACI 2010, Suzhou, China (2010) [E1]
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Nova | |||||||||
2010 |
Hong K, Chalup SK, King RA, 'A component based approach improves classification of discrete facial expressions over a holistic approach', 2010 IEEE World Congress on Computational Intelligence, Barcelona, Spain (2010) [E1]
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Nova | |||||||||
2009 |
Luo S, Jin JS, Chalup SK, Qian G, 'A liver segmentation algorithm based on wavelets and machine learning', Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing, CINC 2009, Wuhan, China (2009) [E1]
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Nova | |||||||||
2009 |
Wiklendt LS, Chalup SK, 'Balance control of a simulated inverted pendulum on a circular base', Proceedings of the 2009 Australasian Conference on Robotics & Automation (ACRA), Sydney, NSW (2009) [E1]
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Nova | |||||||||
2009 |
Ostwald M, Tucker CC, Chalup SK, 'Line segmentation: A computational technique for architectural image analysis', ACADIA 09: reForm (): Building a Better Tomorrow: Proceedings of the 29th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), Chicago, IL (2009) [E1]
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Nova | |||||||||
2009 |
Ostwald M, Vaughan JL, Chalup SK, 'Data-cluster analysis of correlations between facade complexity and orientation in Modernist architecture', Conference Proceedings: 43rd Annual Conference of the Australian and New Zealand Architectural Science Association, Launceston, TAS (2009) [E1]
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Nova | |||||||||
2008 |
Wong AS, Chalup SK, 'Towards visualisation of sound-scapes through dimensionality reduction', IEEE International Joint Conference on Neural Networks, 2008 Proceedings, Hong Kong (2008) [E1]
|
Nova | |||||||||
2008 |
Henderson N, Nicklin SP, Wong AS, Kulk JA, Chalup SK, King R, et al., 'The 2008 NUManoids Team Report', RoboCup. Participating Teams 2008. Downloads, Suzhou, China (2008) [E2]
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2008 |
Henderson N, King RA, Chalup SK, 'An automated colour calibration system using multivariate Gaussian mixtures to segment HSI colour space', Proceedings of the 2008 Australasian Conference on Robotics & Automation, Canberra, ACT (2008) [E1]
|
Nova | |||||||||
2008 |
Wong AS, Chalup SK, 'Sound-scapes for robot localisation through dimensionality reduction', Proceedings of the 2008 Australasian Conference on Robotics & Automation, Canberra, ACT (2008) [E1]
|
Nova | |||||||||
2008 |
Ostwald M, Vaughan JL, Chalup SK, 'A computational analysis of fractal dimensions in the architecture of Eileen Gray', Silicon + Skin: Biological Processes and Computation: Proceedings of the 28th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), Minneapolis, MINN (2008) [E1]
|
Nova | |||||||||
2008 | Chalup SK, Henderson N, Ostwald M, Wiklendt LS, 'A method for cityscape analysis by determining the fractal dimension of its skyline', ANZAScA 2008: Proceedings of the 42nd Annual Conference of the Australian and New Zealand Architectural Science Association, Newcastle, NSW (2008) [E1] | Nova | |||||||||
2008 |
Wiklendt LS, Chalup SK, Seron MM, 'Quadratic leaky integrate-and-fire neural network tuned with an evolution-strategy for a simulated 3D biped walking controller', Proceedings of the 8th International Conference on Hybrid Intelligent Systems, HIS 2008, Barcelona, Spain (2008) [E1]
|
Nova | |||||||||
2008 |
Chalup SK, Hong K, Ostwald M, 'A face-house paradigm for architectural scene analysis', The Fifth International Conference on Soft Computing As Transdisciplinary Science and Technology: Proceedings, Paris, France (2008) [E1]
|
Nova | |||||||||
2007 | Quinlan MJ, Obst O, Chalup SK, 'Towards autonomous strategy decisions in the RoboCup Four-Legged League', 7th IJCAI International Workshop on Nonmontonic Reasoning, Action and Change. Proceedings, Hyderabad, India (2007) [E1] | ||||||||||
2007 |
Lawrence CC, Dickinson MR, Chalup SK, 'Designing charm: Harnessing the affective power of form in robotic development', ConnectED'07, International Conference of Design Education. Proceedings, Sydney (2007) [E1]
|
Nova | |||||||||
2007 |
Tucker CC, Ostwald M, Marshall JP, Chalup SK, 'The visual qualities of liveable streets', Towards Solutions for a Liveable Future: Progress, Practice, Performance, People. Proceedings of the 41st Annual Conference of the Architectural Science Association, Melbourne (2007) [E1]
|
Nova | |||||||||
2007 |
Chalup SK, Clement RM, Marshall JP, Tucker CC, Ostwald M, 'Representations of Streetscape Perceptions Through Manifold Learning in the Space of Hough Arrays', Proceedings of the 2007 IEEE Symposium on Artificial Life (CI-ALife 2007), Honolulu, Hawaii (2007) [E1]
|
Nova | |||||||||
2007 |
Ullrich C, Seese D, Chalup SK, 'Foreign exchange trading with support vector machines', Advances in Data Analysis: Proceedings of the 30th Annual Conference of the Gesellschaft fur Klassifikation e. V., Berlin (2007) [E1]
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2007 |
Chalup SK, Clement RM, Tucker CC, Ostwald M, 'Modelling Architectural Visual Experience Using Non-linear Dimensionality Reduction', Progress in Artificial Life: Third Australian Conference; ACAL 2007 Gold Coast, Australia, December 4-6, 2007 Proceedings, Gold Coast, QLD (2007) [E1]
|
Nova | |||||||||
2006 |
Tucker CC, Ostwald M, Chalup SK, Marshall JP, 'Sustaining Residential Social Space: A Visual and Spatial Analysis of the Nearly Urban', Challenges for Architectural Science in Changing Climates: Proceedings of the 40th Annual Conference of the Architectural Science Association ANZAScA, Adelaide, Australia (2006) [E1]
|
Nova | |||||||||
2006 | Quinlan MJ, Chalup SK, 'Impact of Tactical Variations in the RoboCup Four-Legged League', Proceedings of International Symposium on Practical Cognitive Agents and Robots, Perth, WA, Australia (2006) [E1] | ||||||||||
2006 |
Chalup SK, Dickinson MR, Fisher RD, Middleton RH, Quinlan MJ, Turner PD, 'Proposal of a Kit-Style Robot as the New Standard Platform for the Four-Legged League', Proceedings of the 2006 Australasian Conference on Robotics & Automation, Auckland, New Zealand (2006) [E1]
|
Nova | |||||||||
2005 | Young SR, Chalup SK, 'Towards Robot Soccer Team Behaviours Through Approximate Simulation', Proceedings of 4th IEEE International Conference on Development and Learning, INTEX Osaka, Japan (2005) [E1] | ||||||||||
2005 |
Ullrich C, Seese D, Chalup SK, 'Predicting Foreign Exchange Rate Return Directions with Support Vector Machines', Proceedings of 4th Australasian Data Mining Conference, Sydney (2005) [E1]
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2005 |
Tucker CC, Ostwald M, Chalup SK, Marshall JP, 'A Method for the visual analysis of the streetscape', 5th International Space Syntax Symposium Proceedings Volume II, Delft University of Technology, Netherlands (2005) [E1]
|
Nova | |||||||||
2005 | Dietrich T, Seese D, Chalup SK, 'Difference In Bidding Characteristics On eBay.de', Proceedings of the IADIS e-Commerce 2005, Porto, Portugal (2005) [E1] | ||||||||||
2004 |
Tucker CC, Ostwald M, Chalup SK, 'A Method for the Visual Analysis of Streetscape Character using digital image processing', Contexts of Architecture, Launceston, Tasmania (2004) [E1]
|
Nova | |||||||||
2004 |
Chalup SK, Murch CL, 'Machine learning in the four-legged league', IFAC Proceedings Volumes (IFAC-PapersOnline) (2004) The aim of this work is to contribute some insights and a partial overview of how machine learning methods are used in robotics. We first discuss typical general issues in the rel... [more] The aim of this work is to contribute some insights and a partial overview of how machine learning methods are used in robotics. We first discuss typical general issues in the relationship between robotics and machine learning. Then we locus on projects associated with the RoboCup competition and symposium, and review the extent to which machine learning approaches have been used in the 4-legged league at RoboCup during the years 1998-2003. Further, we summarise the machine learning methods that were used by our own RoboCup team-the NUbots-in 2002/2003.
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2004 | Murch CL, Chalup SK, 'Combining edge detection and colour segmentation in the four-legged league', Australasian Conference on Robotics and Automation (ACRA 2004), Canberra, ACT, Australia (2004) [E1] | Nova | |||||||||
2003 |
Quinlan MJ, Chalup SK, Middleton RH, 'Techniques for Improving Vision and Locomotion on the Sony AIBO Robot', Proceedings for 2003 ARAA, Brisbane (2003) [E1]
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Nova | |||||||||
2003 | Coleman OJ, Chalup SK, 'Towards Matching Perception in Simulated and Real World Robot Navigation', Proceedings for ACAL 2003, Canberra (2003) [E1] | ||||||||||
2003 |
Chang E, Davis J, Chalup S, 'A new look at the enterprise information system life cycle: Introducing the concept of generational change', ICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems (2003) This paper discusses the Enterprise Information System (EIS) life cycle and the phases of the EIS development life cycle. It details the stages in the EIS life cycle and the chara... [more] This paper discusses the Enterprise Information System (EIS) life cycle and the phases of the EIS development life cycle. It details the stages in the EIS life cycle and the characteristics of phases in the system development life cycle and explains where it differs from traditional concepts of software engineering. In particular it defines the concept of generation change and when it is applied to a system. It also describes the nature of the rapid evolution of the EIS and how it results in version or generational change of the system, and how the EIS development life cycle involves a multitude of engineering processes, not just one. This new perspective could lead to the generation of new EIS development methodologies in business modelling, analysis, design, project management and project estimation.
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2003 |
Quinlan MJ, Chalup SK, Middleton RH, 'Application of SVMs for Colour Classification and Collision Detection with AIBO Robots', Proceedings for NIPS 2003, Whistler, BC (2003) [E1]
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2002 | Chalup SK, 'Algorithmic Models of Developmental Learning', Proceedings of the Australian Neuroscience Society 13, Sydney (2002) [E3] | ||||||||||
2002 | Chalup SK, Blair AD, 'Software for Analysing Recurrent Neural Nets that Learn to Predict Non-Regular Languages', Grammatical Inference: Algorithms and Applications, Netherlands (2002) [E1] | ||||||||||
2002 |
Yang J, Estivill-Castro V, Chalup SK, 'Support Vector Clustering Through Proximity Graph Modelling', 9th International Conference on Neural Information Processing, Singapore (2002) [E1]
|
Nova | |||||||||
2001 | Chalup SK, 'Issues of Neurodevelopment in Biological and Artificial Neural Networks', Proceedings of the Fifth Biannual Conference on Artificial Neural Networks and Expert Systems, University of Otago, Dunedin, New Zealand (2001) [E1] | ||||||||||
1999 |
Chalup S, Blair AD, 'Hill climbing in recurrent neural networks for learning the a^n b^n c^n language', Proceedings, 6th International Conference on Neural Information Processing (ICONIP 99), Perth, Western Australia (1999)
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1999 | Chalup SK, 'Design issues in hill climbing for neural network training', Proceedings Australian Conference on Robotics and Automation 1999, Brisbane, Australia (1999) | ||||||||||
1999 | Chalup SK, Maire F, 'A study on hill climbing for neural network training', Proceedings of the 1999 Congress on Evolutionary Computation, Washington D.C,USA (1999) | ||||||||||
1999 |
Chalup S, Maire F, 'A study on hill climbing algorithms for neural network training', Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999 (1999) This study empirically investigates variations of hill climbing algorithms for training artificial neural networks on the 5-bit parity classification task. The experiments compare... [more] This study empirically investigates variations of hill climbing algorithms for training artificial neural networks on the 5-bit parity classification task. The experiments compare the algorithms when they use different combinations of random number distributions, variations in the step size and changes of the neural networks' initial weight distribution. A hill climbing algorithm which uses inline search is proposed. In most experiments on the 5-bit parity task it performed better than simulated annealing and standard hill climbing. © 1999 IEEE.
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1998 | Chalup SK, Hayward R, Diederich J, 'Rule extraction from artificial neural networks trained on elementary number classifcation tasks.', ., The University of Queensland, Brisbane (1998) | ||||||||||
1998 |
Chalup SK, Towsey M, Diederich J, Shellhammer I, Brugman C, 'Natural language learning by recurrent neural networks: A comparison with probabilistic approaches', Proceedings of Joint Conference on New Methods in Language Processing and Computational Natural Language Learning NeMLaP3/CoNLL98, . (1998)
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Show 111 more conferences |
Creative Work (1 outputs)
Year | Citation | Altmetrics | Link | ||
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2013 |
Tucker CC, Chalup S, Lin Y, Haasnoot W, Bille R, Brackenbury J, et al., City Evolutions: Major Morisset, Watt Street, Newcastle, Watt Street, Newcastle (2013) [J2]
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Other (1 outputs)
Year | Citation | Altmetrics | Link | ||
---|---|---|---|---|---|
2019 |
'RoboCup 2019: Robot World Cup XXIII', . Heidelberg: Springer Nature (2019)
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Preprint (1 outputs)
Year | Citation | Altmetrics | Link | |||||
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2022 |
Higgins O, Chalup SK, Short BL, Wilson RL, 'Interpretations of Innovation: The intersection of technological advancement and psychosis (Preprint) (2022)
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Presentation (3 outputs)
Year | Citation | Altmetrics | Link |
---|---|---|---|
2012 | Chalup SK, 'Simulating Mechanisms of Emotion Associated with Visual Perception of Urban Space: An Artificial Agents Perspective', (2012) | ||
2006 | Chalup SK, 'Applications of Manifold Learning in Architectural Facade and Streetscape Analysis', (2006) | ||
2004 | Chalup SK, 'To See or Not to Be in the Four-Legged League', (2004) |
Grants and Funding
Summary
Number of grants | 49 |
---|---|
Total funding | $4,650,684 |
Click on a grant title below to expand the full details for that specific grant.
Highlighted grants and funding
Estimating the Topology of Low-Dimensional Data Using Deep Neural Networks$433,470
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Stephan Chalup, Mr Khalil Hannouch, Mr Dylan Peek |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2021 |
Funding Finish | 2024 |
GNo | G2000134 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design$573,171
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Craig Wheeler, Professor Stephan Chalup, Emeritus Professor Mark Jones, Dr Wei Chen, Paul Cleary, Prof Gabriel Lodewijks, Dr Yusong Pang, Mr Dasun Balasooriya, Dr Wei Chen, Dr Paul Cleary, Mr Tahir Abbas Jauhar, Dr Gabriel Lodewijks, Dr Yusong Pang |
Scheme | Linkage Projects |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2022 |
GNo | G1900355 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
20231 grants / $199,647
BIOMON Stage 1: A pilot biosensor that uses machine learning to identify wildlife acoustically$199,647
Funding body: NSW Environmental Trust
Funding body | NSW Environmental Trust |
---|---|
Project Team | Doctor Andrea Griffin, Professor Matthew Hayward, Professor Stephan Chalup, Doctor Darren Southwell, Doctor Alex Callen, Doctor Sarah Bell, Rye Gollan, Lucas Grenadier, Dr Brad Law, Mr Liam Manning, Reegan Walker, Doctor Sarah Bell, Mr Ian Benson, Luke Foster, Rye Gollan, Mr Lucas Grenadier, Dr Brad Law, Mr Liam Manning, Professor Paul McDonald, Mr Mick Roderick, Reegan Walker, Mr Dan Williams |
Scheme | Environmental Research Program |
Role | Investigator |
Funding Start | 2023 |
Funding Finish | 2025 |
GNo | G2200641 |
Type Of Funding | C1600 - Aust Competitive - StateTerritory Govt |
Category | 1600 |
UON | Y |
20222 grants / $116,420
Improving the Classification of Microstructure Distribution in Coke CT Images using Deep Learning and Lineal Path Calculations$111,020
Funding body: Australian Coal Research Limited
Funding body | Australian Coal Research Limited |
---|---|
Project Team | Doctor Bishnu Lamichhane, Professor Stephan Chalup, Doctor Keith Nesbitt, Associate Professor Merrick Mahoney, Doctor Robert King |
Scheme | Australian Coal Association Research Program (ACARP) |
Role | Investigator |
Funding Start | 2022 |
Funding Finish | 2023 |
GNo | G2101087 |
Type Of Funding | C1700 - Aust Competitive - Other |
Category | 1700 |
UON | Y |
Monitoring algorithm development and reporting application for reducing CO2 emissions from mine site-based fleet vehicles$5,400
Funding body: Leica Geosystems Pty Ltd
Funding body | Leica Geosystems Pty Ltd |
---|---|
Project Team | Doctor Nasimul Noman, Professor Stephan Chalup, Mr Mohammad Mobasher Kashani, Sean Perry |
Scheme | University of Newcastle Industry Training and Engagement (UNITE) Internship |
Role | Investigator |
Funding Start | 2022 |
Funding Finish | 2022 |
GNo | G2200374 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
20214 grants / $878,259
Estimating the Topology of Low-Dimensional Data Using Deep Neural Networks$433,470
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Stephan Chalup, Mr Khalil Hannouch, Mr Dylan Peek |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2021 |
Funding Finish | 2024 |
GNo | G2000134 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
Novel Techniques for Uncoordinated Massive Access in the Internet of Things$421,989
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Sarah Johnson, Associate Professor Kaushik Mahata, Professor Stephan Chalup |
Scheme | Discovery Projects |
Role | Investigator |
Funding Start | 2021 |
Funding Finish | 2023 |
GNo | G2000037 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
Development and Optimization of a Series of Unique AI Algorithms$12,000
Funding body: Pegasus Management Pty Ltd
Funding body | Pegasus Management Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Mr Ali Bakhshi, Mr Adam Van Dyck |
Scheme | University of Newcastle Industry Training and Engagement (UNITE) Internship |
Role | Lead |
Funding Start | 2021 |
Funding Finish | 2021 |
GNo | G2100693 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
To develop and optimise a series of unique AI algorithms (Pegasus Validation Engine) facilities$10,800
Funding body: Pegasus Management Pty Ltd
Funding body | Pegasus Management Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Mr Jake Mullins, Dr Arash Jalalian, Mr Joshua Compton, Mr Ali Bakhshi |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2021 |
Funding Finish | 2021 |
GNo | G2100145 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
20204 grants / $1,372,851
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design$573,171
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Craig Wheeler, Professor Stephan Chalup, Emeritus Professor Mark Jones, Dr Wei Chen, Paul Cleary, Prof Gabriel Lodewijks, Dr Yusong Pang, Mr Dasun Balasooriya, Dr Wei Chen, Dr Paul Cleary, Mr Tahir Abbas Jauhar, Dr Gabriel Lodewijks, Dr Yusong Pang |
Scheme | Linkage Projects |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2022 |
GNo | G1900355 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design$450,000
Funding body: Bradken Limited
Funding body | Bradken Limited |
---|---|
Project Team | Professor Craig Wheeler, Professor Stephan Chalup, Emeritus Professor Mark Jones, Dr Wei Chen, Paul Cleary, Prof Gabriel Lodewijks, Dr Yusong Pang, Doctor Michael Carr, Dr Wei Chen, Dr Paul Cleary, Dr Gabriel Lodewijks |
Scheme | Linkage Projects Partner funding |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2022 |
GNo | G1901027 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Deep learning for MR-only head and neck radiotherapy planning $260,000
Funding body: Varian Medical Systems, Inc.
Funding body | Varian Medical Systems, Inc. |
---|---|
Project Team | Professor Peter Greer, Associate Professor James Welsh, Associate Professor Stephan Chalup, Professor John Simpson |
Scheme | Research Grant |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2022 |
GNo | |
Type Of Funding | International - Non Competitive |
Category | 3IFB |
UON | N |
Correlating the distribution of multiscale structural features with coke quality indicators by combining advanced datamining approaches with 3D visualisation$89,680
Funding body: Australian Coal Research Limited
Funding body | Australian Coal Research Limited |
---|---|
Project Team | Doctor Keith Nesbitt, Professor Stephan Chalup, Professor Karen Blackmore, Doctor Robert King, Associate Professor Merrick Mahoney |
Scheme | Australian Coal Association Research Program (ACARP) |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2021 |
GNo | G1901124 |
Type Of Funding | C1700 - Aust Competitive - Other |
Category | 1700 |
UON | Y |
20198 grants / $260,674
To develop unique control system algorithms and Al for the autonomous operation of trains - Researcher Placement$50,528
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Professor Zhiyong Chen |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2020 |
GNo | G1901187 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
To develop unique control system algorithms and Al for the autonomous operation of trains - Researcher Placement$50,000
Funding body: Department of Industry, Innovation and Science
Funding body | Department of Industry, Innovation and Science |
---|---|
Project Team | Professor Stephan Chalup, Professor Zhiyong Chen |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2020 |
GNo | G1901245 |
Type Of Funding | C2200 - Aust Commonwealth – Other |
Category | 2200 |
UON | Y |
To develop a unique algorithm and interface tool to continuously data mine the captured datasets$49,123
Funding body: Guardvant Pty Ltd
Funding body | Guardvant Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Sean Perry |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2019 |
GNo | G1900527 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
To develop a unique algorithm and interface tool to continuously data mine the captured datasets$49,123
Funding body: Department of Industry, Innovation and Science
Funding body | Department of Industry, Innovation and Science |
---|---|
Project Team | Professor Stephan Chalup, Sean Perry |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2019 |
GNo | G1900780 |
Type Of Funding | C2200 - Aust Commonwealth – Other |
Category | 2200 |
UON | Y |
Ship Design Artificial Intelligence$26,300
Funding body: University of Melbourne
Funding body | University of Melbourne |
---|---|
Project Team | Professor Stephan Chalup, Mr Asad Abbas |
Scheme | AMSI Australian Postgraduate Research Internships |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2019 |
GNo | G1901236 |
Type Of Funding | Scheme excluded from IGS |
Category | EXCL |
UON | Y |
4Tel Platinum Sponsorship - Newcastle Robotics Lab$20,000
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Stephan Chalup |
Scheme | Industry support |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2020 |
GNo | |
Type Of Funding | Not Known |
Category | UNKN |
UON | N |
To develop optimisation algorithms to enhance the utilisation of the Virtual Supply Chain Solution$9,600
Funding body: Traditional Business Online Pty Ltd
Funding body | Traditional Business Online Pty Ltd |
---|---|
Project Team | Associate Professor Stephan Chalup |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2023 |
GNo | |
Type Of Funding | C3111 - Aust For profit |
Category | 3111 |
UON | N |
Mathematical and Machine Learning Aspects of the Visual Mesh$6,000
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Ms Anita Sugo |
Scheme | Research Grant |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2019 |
GNo | G1900149 |
Type Of Funding | C3300 – Aust Philanthropy |
Category | 3300 |
UON | Y |
20182 grants / $79,500
Open Source Discrete Element Method particle Simulation Software Adaption for Vertical Grinding Mill Optimisation$65,000
Funding body: Bradken Resources Pty Limited
Funding body | Bradken Resources Pty Limited |
---|---|
Project Team | Professor Stephan Chalup, Professor Craig Wheeler, Doctor Wei Chen |
Scheme | Research Grant |
Role | Lead |
Funding Start | 2018 |
Funding Finish | 2018 |
GNo | G1800821 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Predictive Analysis of home buyer's readiness to take out a Home Loan$14,500
Funding body: Westpac Banking Corporation
Funding body | Westpac Banking Corporation |
---|---|
Project Team | Professor Stephan Chalup, Professor George Willis |
Scheme | Shared |
Role | Investigator |
Funding Start | 2018 |
Funding Finish | 2018 |
GNo | G1800575 |
Type Of Funding | Scheme excluded from IGS |
Category | EXCL |
UON | Y |
20176 grants / $221,535
Short term solar forecasting over a gridded area using a network of skycams and other sources$118,527
Funding body: CSIRO - Commonwealth Scientific and Industrial Research Organisation
Funding body | CSIRO - Commonwealth Scientific and Industrial Research Organisation |
---|---|
Project Team | Doctor Alexandre Mendes, Professor Stephan Chalup, Mr Sam West, Mr Joel Wong |
Scheme | Postgraduate Scholarship |
Role | Investigator |
Funding Start | 2017 |
Funding Finish | 2020 |
GNo | G1700966 |
Type Of Funding | C2100 - Aust Commonwealth – Own Purpose |
Category | 2100 |
UON | Y |
Efficient data mining and machine learning in high-productivity mining systems$30,000
Funding body: Joy Global Australia Pty Ltd
Funding body | Joy Global Australia Pty Ltd |
---|---|
Project Team | Associate Professor Yuqing Lin, Professor Stephan Chalup, Associate Professor Raymond Chiong |
Scheme | Research Project |
Role | Investigator |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | G1700778 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Vision processing for localization and transport safety – track detection$23,000
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Mr Trent Houliston |
Scheme | Post Graduate Scholarship |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2018 |
GNo | G1701112 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Vision processing for localisation and transport safety - track detection$20,000
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Doctor Alexandre Mendes |
Scheme | Research Grant |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | G1700582 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Automatic Image Analysis for HyLogger - Mineral Mapping$20,000
Funding body: NSW Department of Industry Resources & Energy
Funding body | NSW Department of Industry Resources & Energy |
---|---|
Project Team | Doctor Wei Chen, Doctor Timothy Donohue, Professor Kenneth Williams, Professor Stephan Chalup |
Scheme | Geological Survey of New South Wales |
Role | Investigator |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | G1700660 |
Type Of Funding | C2300 – Aust StateTerritoryLocal – Own Purpose |
Category | 2300 |
UON | Y |
Automatically Fixing Programming Errors through Deep Learning$10,008
Funding body: FEBE Faculty Research Committee
Funding body | FEBE Faculty Research Committee |
---|---|
Project Team | Zhang, Hongyu and Chalup, Stephan |
Scheme | Faculty Strategic Pilot Grant |
Role | Investigator |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20163 grants / $143,756
Project Horus$55,000
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Mr Alexander Biddulph |
Scheme | Research Grant |
Role | Lead |
Funding Start | 2016 |
Funding Finish | 2020 |
GNo | G1601069 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Entrepreneurs Programme - Data Analytics using Kernel machines in Cancer Diagnosis$48,756
Funding body: Department of Industry, Innovation and Science
Funding body | Department of Industry, Innovation and Science |
---|---|
Project Team | Professor Stephan Chalup, Mr Josiah Walker |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2016 |
Funding Finish | 2016 |
GNo | G1601018 |
Type Of Funding | Grant - Aust Non Government |
Category | 3AFG |
UON | Y |
NUbot Team Support: Increase Research in Computer Vision$40,000
Funding body: Local industry
Funding body | Local industry |
---|---|
Project Team | Stephan Chalup |
Scheme | Industry support |
Role | Lead |
Funding Start | 2016 |
Funding Finish | 2016 |
GNo | |
Type Of Funding | Donation - Aust Non Government |
Category | 3AFD |
UON | N |
20151 grants / $5,000
Image Processing Techniques for the Automatic Identification of Available Places in Unstructured Parking Lots$5,000
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Project Team | Alexandre Mendes and Stephan Chalup |
Scheme | Pilot Grant |
Role | Investigator |
Funding Start | 2015 |
Funding Finish | 2015 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20141 grants / $11,611
Applications of Feature Selection Methods for morphological characterization of images and subtypes of brain tumours $11,611
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Project Team | Professor Regina Berretta, Associate Professor Yuqing Lin, Professor Stephan Chalup |
Scheme | Pilot Grant |
Role | Investigator |
Funding Start | 2014 |
Funding Finish | 2014 |
GNo | G1400970 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20132 grants / $278,430
City Evolutions Project - Watt Street$262,430
Funding body: Newcastle City Council
Funding body | Newcastle City Council |
---|---|
Project Team | Doctor Chris Tucker, Conjoint Professor Mark Balnaves, Dr NING Gu, Mr Ramsey Awad, Professor Mario Minichiello, Professor Stephan Chalup, Doctor Keith Nesbitt |
Scheme | Research Grant |
Role | Investigator |
Funding Start | 2013 |
Funding Finish | 2013 |
GNo | G1201004 |
Type Of Funding | Other Public Sector - Local |
Category | 2OPL |
UON | Y |
Paradigm Development for Testing Event Related Potentials Associated with Abstract Face-like Patterns: A New Approach to Design Understanding$16,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Stephan Chalup; Michael Ostwald; Peter Walla |
Scheme | Faculty Grant |
Role | Lead |
Funding Start | 2013 |
Funding Finish | 2013 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20102 grants / $507,032
Modelling and predicting patterns of pedestrian movement: using robotics and machine learning to improve the design of urban space.$486,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Michael Ostwald, Professor Stephan Chalup |
Scheme | Discovery Projects |
Role | Investigator |
Funding Start | 2010 |
Funding Finish | 2012 |
GNo | G0190061 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Neurodynamic programming for sound generation through human-computer interaction$21,032
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Pilot Grant |
Role | Lead |
Funding Start | 2010 |
Funding Finish | 2011 |
GNo | G0900038 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20081 grants / $11,000
Novel liver parenchyma segmentation for liver disease diagnosis using texture analysis and deformable surface models$11,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Associate Professor Suhuai Luo, Professor Stephan Chalup |
Scheme | Pilot Grant |
Role | Investigator |
Funding Start | 2008 |
Funding Finish | 2008 |
GNo | G0189077 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20071 grants / $275,829
Shaping social and cultural spaces: the application of computer visualisation and machine learning techniques to the design of architectural and urban spaces$275,829
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Michael Ostwald, Professor Stephan Chalup |
Scheme | Discovery Projects |
Role | Investigator |
Funding Start | 2007 |
Funding Finish | 2009 |
GNo | G0186245 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
20064 grants / $206,500
Developing computational and algorithmic analytical techniques for investigating urban space$100,000
Funding body: Newcastle Innovation
Funding body | Newcastle Innovation |
---|---|
Project Team | Professor Michael Ostwald, Professor Stephan Chalup, Doctor Chris Tucker |
Scheme | Administered Research |
Role | Investigator |
Funding Start | 2006 |
Funding Finish | 2007 |
GNo | G0188830 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
Developing Computational Analytical Techniques for Investigating Urban, Neighbourhood and Regional Character$95,000
Funding body: TUNRA--McClcoys Industry grant
Funding body | TUNRA--McClcoys Industry grant |
---|---|
Project Team | Ostwald, M.J.; Chalup, S.K.; Tucker, C. |
Scheme | unknown |
Role | Investigator |
Funding Start | 2006 |
Funding Finish | 2006 |
GNo | |
Type Of Funding | Contract - Aust Non Government |
Category | 3AFC |
UON | N |
Rapid Convergence for Reinforcement Learning with Legged Robots$10,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup, Dr Michael Quinlan, Doctor Robert King, Emeritus Professor Rick Middleton |
Scheme | Near Miss Grant |
Role | Lead |
Funding Start | 2006 |
Funding Finish | 2006 |
GNo | G0186068 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
Workshop on New Applications of Dimensionality Reduction at Neural Information Processing Systems NIPS 2006, Vancouver/Whistler Canada, 4/12/2006 - 9/12/2006$1,500
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2006 |
Funding Finish | 2006 |
GNo | G0187215 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20041 grants / $39,319
Application of spiking neural networks to robot locomotion control$39,319
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup, Emeritus Professor Rick Middleton |
Scheme | Multi-Year Project Grant Scholarship |
Role | Lead |
Funding Start | 2004 |
Funding Finish | 2006 |
GNo | G0183487 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20033 grants / $29,730
Robotics Research Network (RRN)$20,000
The RRN brings together all the best robotics research groups in Australia with the aim of fostering and coordinating cooperative research. The RRN integrates researchers from fields including machine perception, sensing, control, artificial intelligence and mechatronics. The RRN includes representation from twelve Universities, CSIRO and involvement of four ARC Centres. Programmes are proposed to share research facilities, to support training of research personnel and promote cooperation in international research programmes. Robotics is already having a substantial impact in industries such as mining and agriculture. Robotics will, in future, offer benefits in areas such as health care, building systems, and defence. https://app.dimensions.ai/details/grant/grant.3578734
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Dr SJ Scheding Dr S Sukkarieh Dr SB Williams Prof HF Durrant-Whyte Dr DJ Austin Dr N Barnes Dr GF Wyeth Dr K Miller Dr AD Blair Dr SK Chalup Dr PI Corke Prof G Dissanayake Dr G Fang Dr T Furukawa Dr QP Ha Prof RA Jarvis A/Prof L Kleeman Dr D Liu |
Scheme | Special Research Initiative |
Role | Investigator |
Funding Start | 2003 |
Funding Finish | 2003 |
GNo | |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | N |
Evaluating the generalisation ability of machine learning classifiers on extreme tasks$8,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Early Career Researcher Grant |
Role | Lead |
Funding Start | 2003 |
Funding Finish | 2003 |
GNo | G0183668 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
17th Annual Conference on Neural Information Processing Systems 8 to 13 December 2003$1,730
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2003 |
Funding Finish | 2003 |
GNo | G0183664 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20021 grants / $2,260
International Conference on Grammatical Inference, Amsterdam 23-25 September 2002$2,260
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2002 |
Funding Finish | 2002 |
GNo | G0182305 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20012 grants / $11,331
Machines Learn via Biologically Motivated Incremental Algorithms$10,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Early Career Researcher Grant |
Role | Lead |
Funding Start | 2001 |
Funding Finish | 2001 |
GNo | G0181591 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
ANNES 2001 New Zealand 22-24 November, 2001$1,331
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2001 |
Funding Finish | 2001 |
GNo | G0181564 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
Research Supervision
Number of supervisions
Current Supervision
Commenced | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2023 | PhD | Intelligent Grinding Mill Simulation and Design | PhD (Mechanical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2022 | PhD | Application of Artificial Intelligence for Efficient Project Management in Smart Buildings | PhD (Building), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2022 | PhD | Zero-Shot Learning for Environmental Audio | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2022 | PhD | Low Dimensional Data Analysis Using Topological Machine Learning | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2022 | PhD | Deep Reinforcement Learning for Grinding Mill Design and Process Optimisation | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2021 | PhD | Topology and Deep Learning | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2021 | PhD | Using Machine Learning to Assist Decision Making in the Assessment of Mental Health Consumers Presenting to Emergency Departments | PhD (Nursing), College of Health, Medicine and Wellbeing, The University of Newcastle | Co-Supervisor |
2020 | PhD | Effects of Neural Activation Topology on Deep Learning | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2019 | PhD | Evolutionary Algorithms for Training Deep Neural Networks | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2018 | PhD | Efficient Stereo Semantic Segmentation for Low Powered Computing Devices | PhD (Computer Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
Past Supervision
Year | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2023 | PhD | Investigation of Methods for Synthetic CT Generation, Evaluation and Implementation for Male and Female Pelvis MRI-only Radiotherapy | PhD (Physics), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2023 | PhD | Empowering Communities through Autonomous Vehicles: A Decentralised Framework for Equitable Integration in Urban Environments | PhD (Architecture), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2023 | PhD | Pose Estimation Neural Networks in the Context of the RoboCup Humanoid League | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2023 | PhD | Artificial Intelligence Techniques to Model the Railway Traffic Management Problem in Tree Topology Railway Networks | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2023 | Masters | Short-term Solar Forecasting Using Sky Camera Backed by a Convolutional Neural Network | M Philosophy(Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2022 | PhD | Deep Learning for Analysis of Time-Series in Smart Home Environments | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2022 | PhD | Deep Reinforcement Learning for Cognitive Radio and Software-Defined Networks | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2021 | PhD | Constraint-based Robust Single- and Multi-Objective Optimization | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2021 | PhD | Affective Analysis of Visual Scenes using Face Pareidolia and Scene-Context | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2021 | PhD | Speech Emotion Recognition Using Deep Neural Networks | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2021 | PhD | Convolutional Neural Networks for Image Segmentation in Clinical Applications | PhD (Electrical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2021 | PhD | Detecting Semi-Transparent Drinking Glasses and Estimating Water Levels Using Deep Learning | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2019 | PhD | Reliability of Interconnection Networks | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2019 | PhD | ORI* On the Aesthetics of Folding and Technology | PhD (Fine Art), College of Human and Social Futures, The University of Newcastle | Co-Supervisor |
2019 | Honours |
Mathematical and Machine Learning Aspects of the Visual Mesh 4Tel Honours research scholarship<br /> |
Computer Science, The University of Newcastle, Faculty of Engineering and built Environment, School of Electrical Engineering and Computing | Sole Supervisor |
2019 | PhD | Manifold Alignment through Deep Autoencoders | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2019 | PhD | Ambient Sensor Fusion for Virtual Reality Systems | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2018 | PhD | Software Architecture and Computer Vision for Resource Constrained Robotics | PhD (Software Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2018 | PhD | Evolutionary Wavelet Neural Networks in Data Classification and Dynamic Control | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2018 | PhD | Topological Analysis, Non-Linear Dimensionality Reduction and Optimisation Applied to Manifolds Represented by Point Clouds | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2018 | Honours | Convolutional Neural Networks and Generative Adversarial Networks for the Detection of Minerals in Drill Core Samples | Computer Science, Faculty of Engineering and Buil Environment, UON | Sole Supervisor |
2017 | Honours |
Machine Learning for Large Datasets University Medal |
Computer Science, UoN | Sole Supervisor |
2017 | PhD | Improved Similarity Search for Large Data in Machine Learning and Robotics | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2016 | PhD | Machine Learning-Based Lung Nodule Detection on Chest X-Ray Radiographs | PhD (Information Technology), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2015 | PhD | Automatic Landmark Detection for Localisation and Navigation | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2015 | Honours |
Uncertainty-Aware Motion Planning for Improved Ball Control in Robot Soccer University Medal<br /> |
Computer Science, Faculty of Engineering and Built Environment - The University of Newcastle (Australia) | Sole Supervisor |
2014 | PhD | Implementing Sensory Perception and Affect on Humanoid Robots Using Applications of Manifold Learning | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2014 | PhD | Feature Selection for Intelligent Transportation Systems | PhD (Information Technology), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2014 | PhD | Cooperative Reinforcement Learning for Independent Learners | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2014 | PhD | Spiking Neural Networks for Robot Locomotion Control | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2014 | Honours |
Electrooculography for Eye Tracking in Head Mounted Displays for Virtual Reality University Medal<br /> |
Computer Science, University of Newcastle | Sole Supervisor |
2013 | PhD | Scene Perception Using Machine Pareidolia of Facial Expressions | PhD (Computer Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2013 | PhD | Multi-Link Mechanical Locomotors in Natural Gaits - Controller Design and Experiments | PhD (Electrical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2013 | Honours |
Investigation of the Properties of the Fractal Mandelbox Sets Universiy Medal<br /> |
Computer Science, University of Newcastle | Sole Supervisor |
2012 | PhD | Estimation of Sparse Distributions | PhD (Electrical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2012 | PhD | Time Series Classification for Analysing the Impact of Architectural Design on Pedestrian Spatial Behaviour | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2012 | Honours | Neuro-Dynamic Programming and Music | Computer Science, Unknown | Sole Supervisor |
2011 | Honours | Support Vector Clustering of Time Series Data with Alignment Kernels | Computr Sc Not Elswhere Class, Karlsruhe Institute of Technology | Principal Supervisor |
2008 | PhD | A Learning Classifier System Approach to Relational Reinforcement Learning | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2006 | PhD | Machine Learning on AIBO Robots | PhD (Software Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2006 | Honours | Research and Assistance Into Rescue Robot | Computer Engineering, University of Newcastle | Sole Supervisor |
2006 | Honours | Machine Learning Autonomous Aircraft Agent in a Simulation | Computer Engineering, University of Newcastle | Sole Supervisor |
2006 | Honours | Autonomous Aircraft in a Simulation | Computer Engineering, University of Newcastle | Sole Supervisor |
2005 | Honours | A Simulator for Learning to Play Robot Soccer | Computr Sc Not Elswhere Class, University of Newcastle | Sole Supervisor |
2004 | Honours | Consciousness in Artificial Neural Networks | Computer Science, University of Newcastle | Sole Supervisor |
2004 | Honours |
Dimensionality Reduction on AIBO Robots University Medal<br /> |
Computer Science, University of Newcastle | Sole Supervisor |
Research Projects
Reinforcement Learning 2001 -
This project comprises several focused case studies involving reinforcement learning. We are currently investigating deep reinforcement learning in the domain of network optimisation.
Grants
Machines Learn via Biologically Motivated Incremental Algorithms
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Early Career Researcher Grant |
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Mr Dasun Balasooriya, Dr Wei Chen, Dr Paul Cleary, Mr Tahir Abbas Jauhar, Dr Gabriel Lodewijks, Dr Yusong Pang, Professor Craig Wheeler, Professor Stephan Chalup, Emeritus Professor Mark Jones, Dr Wei Chen, Paul Cleary, Prof Gabriel Lodewijks, Dr Yusong Pang |
Scheme | Linkage Projects |
Rapid Convergence for Reinforcement Learning with Legged Robots
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup, Dr Michael Quinlan, Doctor Robert King, Emeritus Professor Rick Middleton |
Scheme | Near Miss Grant |
Neurodynamic programming for sound generation through human-computer interaction
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Pilot Grant |
Publications
Wiklendt LS, Chalup SK, 'Balance control of a simulated inverted pendulum on a circular base', Proceedings of the 2009 Australasian Conference on Robotics & Automation (ACRA), Sydney, NSW (2009) [E1]
Fountain J, Walker J, Budden D, Mendes A, Chalup SK, 'Motivated reinforcement learning for improved head actuation of humanoid robots', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2014) [E1]
Abed-alguni BH, Chalup SK, Henskens FA, Paul DJ, 'A multi-agent cooperative reinforcement learning model using a hierarchy of consultants, tutors and workers', Vietnam Journal of Computer Science, 2 213-226 (2015) [C1]
Walker J, Chalup SK, 'Learning Nursery Rhymes using Adaptive Parameter Neurodynamic Programming', Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015. Proceedings, Newcastle, Australia (2015) [E1]
Abed-Alguni B, Paul D, Chalup S, Henskens FA, 'A Comparison Study of Cooperative Q-learning Algorithms for Independent Learners', International Journal of Artificial Intelligence, 14 71-93 (2016) [C1]
Jalil SQ, Husain Rehmani M, Chalup S, 'DQR: Deep Q-Routing in Software Defined Networks', Proceedings of the 2020 International Joint Conference on Neural Networks, Glasgow, United Kingdom (2020) [E1]
Students
Program | Research Title |
---|---|
PhD College of Engineering, Science and Environment |
Effects of Neural Activation Topology on Deep Learning |
PhD College of Engineering, Science and Environment |
Cooperative Reinforcement Learning for Independent Learners |
Honours Unknown |
Neuro-Dynamic Programming and Music |
PhD College of Engineering, Science and Environment |
A Learning Classifier System Approach to Relational Reinforcement Learning |
PhD College of Engineering, Science and Environment |
Spiking Neural Networks for Robot Locomotion Control |
Honours University of Newcastle |
Electrooculography for Eye Tracking in Head Mounted Displays for Virtual Reality University Medal<br /> |
Honours Faculty of Engineering and Buil Environment, UON |
Convolutional Neural Networks and Generative Adversarial Networks for the Detection of Minerals in Drill Core Samples |
PhD College of Engineering, Science and Environment |
Artificial Intelligence Techniques to Model the Railway Traffic Management Problem in Tree Topology Railway Networks |
PhD College of Engineering, Science and Environment |
Deep Reinforcement Learning for Cognitive Radio and Software-Defined Networks |
Artificial Neural Networks and Deep Learning 1997 -
In this long-term project we investigate artificial neural networks. This includes the design, implementation, testing and application of new neural network models, robust training schemes and also the investigation of their inner workings.
In the first period we investigated, for example, how to extract logical rules from trained artificial neural networks (Chalup et al., 1998). We were able to train the first recurrent neural networks that could process a context-sensitive language (Chalup and Blair, 1999). This was followed by a dynamical systems analysis of the hidden unit space of recurrent neural networks processing symbol sequences (Chalup and Blair, 2003).
More recently we developed new deep neural networks or contributed to their analysis. The Visual Mesh is one of the fastest object detectors that can run on low powered devices (Houliston and Chalup, 2019). (Asad and Chalup, 2019) analysed the hidden layers of CNNs and demonstrated that they can perform artificial facial pareidolia. In deep learning we contributed to the areas of computer vision, image processing, manifold learning, high dimensional data analysis and control.
Grants
Project Horus
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Mr Alexander Biddulph |
Scheme | Research Grant |
Mathematical and Machine Learning Aspects of the Visual Mesh
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Ms Anita Sugo |
Scheme | Research Grant |
Machines Learn via Biologically Motivated Incremental Algorithms
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Early Career Researcher Grant |
International Conference on Grammatical Inference, Amsterdam 23-25 September 2002
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Automatically Fixing Programming Errors through Deep Learning
Funding body: FEBE Faculty Research Committee
Funding body | FEBE Faculty Research Committee |
---|---|
Scheme | Faculty Strategic Pilot Grant |
Application of spiking neural networks to robot locomotion control
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup, Emeritus Professor Rick Middleton |
Scheme | Multi-Year Project Grant Scholarship |
17th Annual Conference on Neural Information Processing Systems 8 to 13 December 2003
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Efficient data mining and machine learning in high-productivity mining systems
Funding body: Joy Global Australia Pty Ltd
Funding body | Joy Global Australia Pty Ltd |
---|---|
Project Team | Associate Professor Yuqing Lin, Professor Stephan Chalup, Associate Professor Raymond Chiong |
Scheme | Research Project |
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Mr Dasun Balasooriya, Dr Wei Chen, Dr Paul Cleary, Mr Tahir Abbas Jauhar, Dr Gabriel Lodewijks, Dr Yusong Pang, Professor Craig Wheeler, Professor Stephan Chalup, Emeritus Professor Mark Jones, Dr Wei Chen, Paul Cleary, Prof Gabriel Lodewijks, Dr Yusong Pang |
Scheme | Linkage Projects |
Workshop on New Applications of Dimensionality Reduction at Neural Information Processing Systems NIPS 2006, Vancouver/Whistler Canada, 4/12/2006 - 9/12/2006
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Vision processing for localisation and transport safety - track detection
Funding body: 4Tel Pty Ltd
Funding body | 4Tel Pty Ltd |
---|---|
Project Team | Professor Stephan Chalup, Doctor Alexandre Mendes |
Scheme | Research Grant |
Automatic Image Analysis for HyLogger - Mineral Mapping
Funding body: NSW Department of Industry Resources & Energy
Funding body | NSW Department of Industry Resources & Energy |
---|---|
Project Team | Doctor Wei Chen, Doctor Timothy Donohue, Professor Kenneth Williams, Professor Stephan Chalup |
Scheme | Geological Survey of New South Wales |
Predictive Analysis of home buyer's readiness to take out a Home Loan
Funding body: Westpac Banking Corporation
Funding body | Westpac Banking Corporation |
---|---|
Project Team | Professor Stephan Chalup, Professor George Willis |
Scheme | Shared |
Image Processing Techniques for the Automatic Identification of Available Places in Unstructured Parking Lots
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Scheme | Pilot Grant |
Short term solar forecasting over a gridded area using a network of skycams and other sources
Funding body: CSIRO - Commonwealth Scientific and Industrial Research Organisation
Funding body | CSIRO - Commonwealth Scientific and Industrial Research Organisation |
---|---|
Project Team | Doctor Alexandre Mendes, Professor Stephan Chalup, Mr Sam West, Mr Joel Wong |
Scheme | Postgraduate Scholarship |
Publications
Chalup SK, Hayward R, Diederich J, 'Rule extraction from artificial neural networks trained on elementary number classifcation tasks.', ., The University of Queensland, Brisbane (1998)
Chalup S, Maire F, 'A study on hill climbing algorithms for neural network training', Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999 (1999)
Chalup S, Blair AD, 'Hill climbing in recurrent neural networks for learning the a^n b^n c^n language', Proceedings, 6th International Conference on Neural Information Processing (ICONIP 99), Perth, Western Australia (1999)
Chalup SK, 'Issues of Neurodevelopment in Biological and Artificial Neural Networks', Proceedings of the Fifth Biannual Conference on Artificial Neural Networks and Expert Systems, University of Otago, Dunedin, New Zealand (2001) [E1]
Chalup SK, 'Incremental Learning in Biological and Machine Learning Systems', International Journal of Neural Systems, 12 447-465 (2002) [C1]
Chalup SK, Blair AD, 'Incremental training of first order recurrent neural networks to predict a context-sensitive language', Neural Networks, 16 955-972 (2003) [C1]
Wiklendt LS, Chalup SK, Seron MM, 'Quadratic leaky integrate-and-fire neural network tuned with an evolution-strategy for a simulated 3D biped walking controller', Proceedings of the 8th International Conference on Hybrid Intelligent Systems, HIS 2008, Barcelona, Spain (2008) [E1]
Wiklendt LS, Chalup SK, Middleton RH, 'A small spiking neural network with LQR control applied to the acrobot', Neural Computing & Applications, 18 369-375 (2009) [C1]
Wiklendt LS, Chalup SK, Seron MM, 'Simulated 3D biped walking with an evolution-strategy tuned spiking neural network', Neural Network World, 19 235-246 (2009) [C1]
Khan MM, Chalup SK, Mendes A, 'Evolving Wavelet Neural Networks for Breast Cancer Classification', Conferences in Research Practice and Information Technology, Brisbane, Qld (2014) [E1]
Khan M, Chalup S, Mendes A, 'Evolving wavelet neural networks for breast cancer classification', Conferences in Research and Practice in Information Technology Series (2014)
Khan MM, Mendes A, Zhang P, Chalup SK, 'Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming', NEUROCOMPUTING, 247 39-58 (2017) [C1]
Jabbar A, Farrawell L, Fountain J, Chalup SK, 'Training Deep Neural Networks for Detecting Drinking Glasses using Synthetic Images', Neural Information Processing. 24th International Conference, ICONIP 2017, Guangzhou, China (2017) [E1]
Khan MM, Mendes A, Chalup SK, 'Evolutionary wavelet neural network ensembles for breast cancer and Parkinson s disease prediction', PLoS ONE, 13 (2018) [C1]
Biddulph A, Houliston T, Mendes A, Chalup SK, 'Comparing Computing Platforms for Deep Learning on a Humanoid Robot', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Siem Reap, Cambodia (2018) [E1]
Students
Program | Research Title |
---|---|
PhD College of Engineering, Science and Environment |
Investigation of Methods for Synthetic CT Generation, Evaluation and Implementation for Male and Female Pelvis MRI-only Radiotherapy |
PhD College of Engineering, Science and Environment |
Software Architecture and Computer Vision for Resource Constrained Robotics |
PhD College of Engineering, Science and Environment |
Evolutionary Algorithms for Training Deep Neural Networks |
Honours UoN |
Machine Learning for Large Datasets University Medal |
PhD College of Engineering, Science and Environment |
Affective Analysis of Visual Scenes using Face Pareidolia and Scene-Context |
PhD College of Engineering, Science and Environment |
Speech Emotion Recognition Using Deep Neural Networks |
PhD College of Engineering, Science and Environment |
Evolutionary Wavelet Neural Networks in Data Classification and Dynamic Control |
PhD College of Engineering, Science and Environment |
Topological Analysis, Non-Linear Dimensionality Reduction and Optimisation Applied to Manifolds Represented by Point Clouds |
PhD College of Engineering, Science and Environment |
Manifold Alignment through Deep Autoencoders |
Honours University of Newcastle |
Consciousness in Artificial Neural Networks |
PhD College of Engineering, Science and Environment |
Convolutional Neural Networks for Image Segmentation in Clinical Applications |
PhD College of Engineering, Science and Environment |
Pose Estimation Neural Networks in the Context of the RoboCup Humanoid League |
PhD College of Engineering, Science and Environment |
Spiking Neural Networks for Robot Locomotion Control |
Honours Faculty of Engineering and Buil Environment, UON |
Convolutional Neural Networks and Generative Adversarial Networks for the Detection of Minerals in Drill Core Samples |
PhD College of Engineering, Science and Environment |
Detecting Semi-Transparent Drinking Glasses and Estimating Water Levels Using Deep Learning |
Opportunities
Machine Learning for Topological and Geometrical Data Analysis
This topic has several subprojects, including concept development, simulation experiments and applications. High-dimensional data is common in many applications. Abstractly it can have fascinating properties that are different from what we are used to when using our spatial intuition. In many cases non-linear dimensionality reduction (or manifold learning) can without loss of information reduce high-dimensional data to lower dimensions. Hence, we specifically look at a range of machine learning and other techniques that can be used to analyse 3- and 4-dimensional data that cannot be further reduced in dimension and exhibits a level of complexity that is beyond average human visual understanding. Our project team welcomes enquiries by prospective Honours, FYP, Masters or PhD students. Start and end dates are flexible from our side. We are also interested in expanding our collaborations in academia and industry and in any suggestions of data. Please contact Stephan Chalup for further details.
Other
2023 - 2028
Contact
Professor Stephan Chalup
stephan.chalup@newcastle.edu.au
Artificial Intelligence and Machine Learning in Applications
In this project area we address a range of interdisciplinary applications of Artificial Intelligence and Machine Learning in industry or at university. The project is suitable for Honours, FYP, Masters or PhD students. Start and end dates are flexible. Please contact Stephan Chalup for further details.
Other
2023 - 2024
Contact
Professor Stephan Chalup
stephan.chalup@newcastle.edu.au
Geometrical and Topological Analysis of 3D and High-Dimensional Data 2006 -
In this long-term project we analyse the structure of three-dimensional and other high-dimensional data using computational and mathematical techniques. We investigate and apply techniques of non-linear dimensionality reduction, manifold alignment and computational topology. Several PhD students have successfully completed their theses in this domain. We are currently expanding this area in collaboration with two of our priority research centres (CDSC and CARMA) and several colleagues who are specialised on visualisation and VR. Application data has been provided so far from material science, coal and rock data, medical scan data as well as simulated data for benchmarking. Our interdisciplinary expert team has recently developed a number of new approaches. We also have obtained new local supercomputing hardware that supports this growing project area.
Topics of new PhD students are available and top-up scholarships can be negotiated.
Grants
Generative Adversarial Learning for Recognising Deformations of Complex High-Dimensional Data
Funding body: Priority Research Center for Complex Dynamic Systems and Control (PRC CDSC)
Funding body | Priority Research Center for Complex Dynamic Systems and Control (PRC CDSC) |
---|---|
Scheme | 2019 CDSC Undergraduate Research Project |
Estimating the Topology of Low-Dimensional Data Using Deep Neural Networks
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Mr Khalil Hannouch, Mr Dylan Peek, Professor Stephan Chalup |
Scheme | Discovery Projects |
Workshop on New Applications of Dimensionality Reduction at Neural Information Processing Systems NIPS 2006, Vancouver/Whistler Canada, 4/12/2006 - 9/12/2006
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
2007 IEEE Symposium on Artificial Life, Honolulu Hawaii, 31/3/2007 - 6/4/2007
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Shaping social and cultural spaces: the application of computer visualisation and machine learning techniques to the design of architectural and urban spaces
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Michael Ostwald, Professor Stephan Chalup |
Scheme | Discovery Projects |
Publications
Chalup SK, 'Applications of Manifold Learning in Architectural Facade and Streetscape Analysis', (2006)
Chalup SK, Clement RM, Tucker CC, Ostwald M, 'Modelling Architectural Visual Experience Using Non-linear Dimensionality Reduction', Progress in Artificial Life: Third Australian Conference; ACAL 2007 Gold Coast, Australia, December 4-6, 2007 Proceedings, Gold Coast, QLD (2007) [E1]
Chalup SK, Clement RM, Marshall JP, Tucker CC, Ostwald M, 'Representations of Streetscape Perceptions Through Manifold Learning in the Space of Hough Arrays', Proceedings of the 2007 IEEE Symposium on Artificial Life (CI-ALife 2007), Honolulu, Hawaii (2007) [E1]
Wong AS, Chalup SK, 'Sound-scapes for robot localisation through dimensionality reduction', Proceedings of the 2008 Australasian Conference on Robotics & Automation, Canberra, ACT (2008) [E1]
Wong AS, Chalup SK, 'Towards visualisation of sound-scapes through dimensionality reduction', IEEE International Joint Conference on Neural Networks, 2008 Proceedings, Hong Kong (2008) [E1]
Chalup SK, Henderson N, Ostwald M, Wiklendt LS, 'A computational approach to fractal analysis of a cityscape's skyline', Architectural Science Review, 52 126-134 (2009) [C1]
Wong AS, Chalup SK, Bhatia S, Jalalian A, Kulk JA, Ostwald M, 'Humanoid robots for modelling and analysing visual gaze dynamics of pedestrians moving in urban space', Conference Proceedings 45th Annual Conference of the Australian and New Zealand Architectural Science Association, Sydney, NSW (2011) [E1]
Wong AS, Chalup SK, Bhatia S, Jalalian A, Kulk JA, Nicklin SP, Ostwald M, 'Visual gaze analysis of robotic pedestrians moving in urban space', Architectural Science Review, 55 213-223 (2012) [C1]
Paul R, Chalup SK, 'A Study on Validating Non-Linear Dimensionality Reduction using Persistent Homology', Pattern Recognition Letters, 100 160-166 (2017) [C1]
Aziz F, Wong ASW, Welsh JS, Chalup SK, 'Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Siem Reap, Cambodia (2018) [E1]
Aziz F, Wong ASW, Chalup S, 'Semi-Supervised Manifold Alignment Using Parallel Deep Autoencoders', Algorithms, 12 186-186 (2019) [C1]
Paul R, Chalup S, 'Estimating Betti numbers using deep learning', 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary (2019) [E1]
Students
Program | Research Title |
---|---|
PhD College of Engineering, Science and Environment |
Implementing Sensory Perception and Affect on Humanoid Robots Using Applications of Manifold Learning |
PhD College of Engineering, Science and Environment |
Improved Similarity Search for Large Data in Machine Learning and Robotics |
PhD College of Engineering, Science and Environment |
Topological Analysis, Non-Linear Dimensionality Reduction and Optimisation Applied to Manifolds Represented by Point Clouds |
PhD College of Engineering, Science and Environment |
Manifold Alignment through Deep Autoencoders |
Honours University of Newcastle |
Dimensionality Reduction on AIBO Robots University Medal<br /> |
Honours University of Newcastle |
Electrooculography for Eye Tracking in Head Mounted Displays for Virtual Reality University Medal<br /> |
Honours Faculty of Engineering and Buil Environment, UON |
Convolutional Neural Networks and Generative Adversarial Networks for the Detection of Minerals in Drill Core Samples |
PhD College of Engineering, Science and Environment |
Ambient Sensor Fusion for Virtual Reality Systems |
Collaborators
Name | Organisation |
---|---|
Doctor Keith Vincent Nesbitt | University of Newcastle |
Opportunities
Machine Learning for Topological and Geometrical Data Analysis
This topic has several subprojects, including concept development, simulation experiments and applications. High-dimensional data is common in many applications. Abstractly it can have fascinating properties that are different from what we are used to when using our spatial intuition. In many cases non-linear dimensionality reduction (or manifold learning) can without loss of information reduce high-dimensional data to lower dimensions. Hence, we specifically look at a range of machine learning and other techniques that can be used to analyse 3- and 4-dimensional data that cannot be further reduced in dimension and exhibits a level of complexity that is beyond average human visual understanding. Our project team welcomes enquiries by prospective Honours, FYP, Masters or PhD students. Start and end dates are flexible from our side. We are also interested in expanding our collaborations in academia and industry and in any suggestions of data. Please contact Stephan Chalup for further details.
Other
2023 - 2028
Contact
Professor Stephan Chalup
stephan.chalup@newcastle.edu.au
Kernel Machines and Interdisciplinary Applications 2004 - 2020
This project addressed the evaluation and application of kernel machines using a range of interdisciplinary applications. Amon the main achievements in this domain was the first implementation of SVMs on small low-powered robots, studies on the efficiency of support vector clustering and the application of time-series kernels.
Grants
Evaluating the generalisation ability of machine learning classifiers on extreme tasks
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Early Career Researcher Grant |
Modelling and predicting patterns of pedestrian movement: using robotics and machine learning to improve the design of urban space.
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Michael Ostwald, Professor Stephan Chalup |
Scheme | Discovery Projects |
Entrepreneurs Programme - Data Analytics using Kernel machines in Cancer Diagnosis
Funding body: Department of Industry, Innovation and Science
Funding body | Department of Industry, Innovation and Science |
---|---|
Description | TruScreen Pty Ltd |
Project Team | Professor Stephan Chalup, Mr Josiah Walker |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Publications
Yang J, Estivill-Castro V, Chalup SK, 'Support Vector Clustering Through Proximity Graph Modelling', 9th International Conference on Neural Information Processing, Singapore (2002) [E1]
Quinlan MJ, Chalup SK, Middleton RH, 'Techniques for Improving Vision and Locomotion on the Sony AIBO Robot', Proceedings for 2003 ARAA, Brisbane (2003) [E1]
Quinlan MJ, Chalup SK, Middleton RH, 'Application of SVMs for Colour Classification and Collision Detection with AIBO Robots', Proceedings for NIPS 2003, Whistler, BC (2003) [E1]
Middleton RH, Chalup SK, Quinlan MJ, Murch CL, 'Traction monitoring for collision detection with legged robots', Lecture Notes in Artificial Intelligence, 3020 374-384 (2004) [C1]
Ullrich C, Seese D, Chalup SK, 'Predicting Foreign Exchange Rate Return Directions with Support Vector Machines', Proceedings of 4th Australasian Data Mining Conference, Sydney (2005) [E1]
Chalup SK, Wiklendt LS, 'Variations of the two-spiral task', Connection Science, 19 183-199 (2007) [C1]
Chalup SK, Murch CL, Quinlan MJ, 'Machine learning with AIBO robots in the four-legged league of RoboCup', IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 37 297-310 (2007) [C1]
Ullrich C, Seese D, Chalup SK, 'Foreign exchange trading with support vector machines', Advances in Data Analysis: Proceedings of the 30th Annual Conference of the Gesellschaft fur Klassifikation e. V., Berlin (2007) [E1]
Chalup SK, Mitschele A, 'Kernel methods in finance', Handbook on Information Technology in Finance, Springer, Berlin 655-687 (2008) [B1]
Goldsmith BE, Chalup SK, Quinlan MJ, 'Regime type and international conflict: Towards a general model', Journal of Peace Research, 45 743-763 (2008) [C1]
Bozic C, Chalup SK, Detlef S, 'Application of intelligent systems for news analytics', Financial Decision Making Using Computational Intelligence, Springer, New York 71-101 (2012) [B1]
Hong K, Chalup SK, King RA, 'An experimental evaluation of pairwise adaptive support vector machines', Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), Brisbane (2012) [E1]
Jalalian A, Chalup SK, Ostwald M, 'Analysis of pedestrian spatial behaviour using GDTW-P-SVMs', Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), Brisbane (2012) [E1]
Jalalian A, Chalup SK, 'GDTW-P-SVMs: Variable-length time series analysis using support vector machines', NEUROCOMPUTING, 99 270-282 (2013) [C1]
Hong K, Chalup SK, King RAR, 'A component based approach for classifying the seven universal facial expressions of emotion', Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing, CICAC 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, Singapore (2013) [E1]
Hong K, Chalup SK, King RAR, Ostwald MJ, 'Scene Perception using Pareidolia of Faces and Expressions of Emotion', Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC), Singapore, SINGAPORE (2013) [E1]
Hong K, Chalup SK, King RAR, 'Affective visual perception using machine pareidolia of facial expressions', IEEE Transactions on Affective Computing, 5 352-363 (2014) [C1]
Boecking B, Chalup SK, Seese D, Wong ASW, 'Support vector clustering of time series data with alignment kernels', Pattern Recognition Letters, 45 129-135 (2014) [C1]
Students
Program | Research Title |
---|---|
PhD College of Engineering, Science and Environment |
Scene Perception Using Machine Pareidolia of Facial Expressions |
PhD College of Engineering, Science and Environment |
Time Series Classification for Analysing the Impact of Architectural Design on Pedestrian Spatial Behaviour |
PhD College of Engineering, Science and Environment |
Machine Learning on AIBO Robots |
Honours Karlsruhe Institute of Technology |
Support Vector Clustering of Time Series Data with Alignment Kernels |
Medical Pattern Recognition 2010 -
Our research in medical pattern recognition employs machine learning for various aspects of medical image and data analysis. The focus is on the application and development of new and state-of-the art technologies. In recent years deep learning has become of central importance. Another application domain has been technology development for the aged care and independent living domain.
Grants
ANNES 2001 New Zealand 22-24 November, 2001
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup |
Scheme | Travel Grant |
Application of spiking neural networks to robot locomotion control
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Stephan Chalup, Emeritus Professor Rick Middleton |
Scheme | Multi-Year Project Grant Scholarship |
Deep learning for MR-only head and neck radiotherapy planning
Funding body: Varian Medical Systems, Inc.
Funding body | Varian Medical Systems, Inc. |
---|---|
Scheme | Research Grant |
Novel liver parenchyma segmentation for liver disease diagnosis using texture analysis and deformable surface models
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Associate Professor Suhuai Luo, Professor Stephan Chalup |
Scheme | Pilot Grant |
Project EVA: an environmentally responsible facility for interdisciplinary supercomputing applications
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Pablo Moscato, Professor Regina Berretta, Laureate Professor Jon Borwein, Conjoint Professor Keith Jones, Conjoint Professor Chris Levi, Professor Mark Parsons, Professor Michael Ostwald, Emeritus Professor Hugh Craig, Conjoint Professor Peter Greer, Professor Stephan Chalup |
Scheme | Equipment Grant |
Entrepreneurs Programme - Data Analytics using Kernel machines in Cancer Diagnosis
Funding body: Department of Industry, Innovation and Science
Funding body | Department of Industry, Innovation and Science |
---|---|
Description | TruScreen Pty Ltd |
Project Team | Professor Stephan Chalup, Mr Josiah Walker |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Publications
Chalup SK, 'Algorithmic Models of Developmental Learning', Proceedings of the Australian Neuroscience Society 13, Sydney (2002) [E3]
Chalup SK, Middleton RH, Quinlan MJ, Wiklendt LS, 'Neurocomputational aspects of legged locomotion motor control', Proceedings of the Australian Neuroscience Society, 15 105 (2004) [C3]
Luo S, Jin JS, Chalup SK, Qian G, 'A liver segmentation algorithm based on wavelets and machine learning', Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing, CINC 2009, Wuhan, China (2009) [E1]
Fountain J, Chalup SK, 'Point of regard from eye velocity in stereoscopic virtual environments based on intersections of hypothesis surfaces', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2015) [E1]
Khan MM, Chalup SK, Mendes A, 'Parkinson s disease data classification using evolvable wavelet neural networks', Artificial Life and Computational Intelligence. Second Australasian Conference, ACALCI 2016, Canberra, Australia (2016) [E1]
Abbas A, Chalup SK, 'Group Emotion Recognition in the Wild by Combining Deep Neural Networks for Facial Expression Classification and Scene Context Analysis', ICMI 17, Proceedings of the 19th ACM International Conference on Multimodal Interaction, Glasgow, Scotland (2017) [E1]
Astono I, Welsh JS, Chalup S, 'Adjacent Network for Semantic Segmentation of Liver CT Scans', PROCEEDINGS 2018 IEEE 18TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE), TAIWAN, Taichung (2018) [E1]
Choi JH, Lee D, O'Connor L, Chalup S, Welsh JS, Dowling J, Greer PB, 'Bulk Anatomical Density Based Dose Calculation for Patient-Specific Quality Assurance of MRI-Only Prostate Radiotherapy', Frontiers in Oncology, 9 (2019) [C1]
Astono IP, Welsh JS, Chalup S, Greer P, 'Optimisation of 2D U-Net Model Components for Automatic Prostate Segmentation on MRI', Applied Sciences, 10 (2020) [C1]
Gholizadeh N, Simpson J, Ramadan S, Denham J, Lau P, Siddique S, et al., 'Voxel-based supervised machine learning of peripheral zone prostate cancer using noncontrast multiparametric MRI', Journal of Applied Clinical Medical Physics, 21 179-191 (2020) [C1]
Students
Program | Research Title |
---|---|
PhD College of Engineering, Science and Environment |
Investigation of Methods for Synthetic CT Generation, Evaluation and Implementation for Male and Female Pelvis MRI-only Radiotherapy |
PhD College of Engineering, Science and Environment |
Implementing Sensory Perception and Affect on Humanoid Robots Using Applications of Manifold Learning |
PhD College of Engineering, Science and Environment |
Speech Emotion Recognition Using Deep Neural Networks |
PhD College of Engineering, Science and Environment |
Machine Learning-Based Lung Nodule Detection on Chest X-Ray Radiographs |
PhD College of Engineering, Science and Environment |
Evolutionary Wavelet Neural Networks in Data Classification and Dynamic Control |
PhD College of Engineering, Science and Environment |
Manifold Alignment through Deep Autoencoders |
PhD College of Engineering, Science and Environment |
Convolutional Neural Networks for Image Segmentation in Clinical Applications |
PhD College of Engineering, Science and Environment |
Detecting Semi-Transparent Drinking Glasses and Estimating Water Levels Using Deep Learning |
Collaborators
Name | Organisation |
---|---|
Conjoint Professor Peter Brian Greer | |
Doctor John Simpson | |
Doctor Aaron Seng Wai Wong | University of Newcastle |
Edit
Research Opportunities
Machine Learning for Topological and Geometrical Data Analysis
This topic has several subprojects, including concept development, simulation experiments and applications. High-dimensional data is common in many applications. Abstractly it can have fascinating properties that are different from what we are used to when using our spatial intuition. In many cases non-linear dimensionality reduction (or manifold learning) can without loss of information reduce high-dimensional data to lower dimensions. Hence, we specifically look at a range of machine learning and other techniques that can be used to analyse 3- and 4-dimensional data that cannot be further reduced in dimension and exhibits a level of complexity that is beyond average human visual understanding. Our project team welcomes enquiries by prospective Honours, FYP, Masters or PhD students. Start and end dates are flexible from our side. We are also interested in expanding our collaborations in academia and industry and in any suggestions of data. Please contact Stephan Chalup for further details.
Other
Interdisciplinary Machine Learning Research Group
1/12/2023 - 31/12/2028
Contact
Professor Stephan Chalup
University of Newcastle
School of Information and Physical Sciences
stephan.chalup@newcastle.edu.au
PhD: Neural Principles of Multi-Sensor Vision Systems in Rail Safety Applications
The project will develop new deep learning methods to improve machine vision comprising several sensors in collaboration with industry partners 4AI Systems and 4Tel Pty Ltd.
PHD
Newcastle Robotics Lab
1/7/2024 - 31/12/2027
Contact
Professor Stephan Chalup
University of Newcastle
School of Information and Physical Sciences
stephan.chalup@newcastle.edu.au
Postdoc in Computational Shape Optimisation
As part of out ARC Linkage project we offer an about 1 year postdoc level position in the area of computational shape optimisation and deep reinforcement learning. The position requires a highly-skilled expert who can support our already running team as soon as possible.
Postdoctoral
College of Engineering, Science and Environment
1/5/2024 - 31/12/2024
Contact
Professor Stephan Chalup
University of Newcastle
School of Information and Physical Sciences
stephan.chalup@newcastle.edu.au
PhD: Neural Principles of Multi-Sensor Vision Systems in Rail Safety Applications
The project will develop new deep learning methods to improve machine vision comprising several sensors in collaboration with industry partners 4AI Systems and 4Tel Pty Ltd.
PHD
Newcastle Robotics Lab
1/7/2024 - 31/12/2027
Contact
Professor Stephan Chalup
University of Newcastle
School of Information and Physical Sciences
stephan.chalup@newcastle.edu.au
Artificial Intelligence and Machine Learning in Applications
In this project area we address a range of interdisciplinary applications of Artificial Intelligence and Machine Learning in industry or at university. The project is suitable for Honours, FYP, Masters or PhD students. Start and end dates are flexible. Please contact Stephan Chalup for further details.
Other
Newcastle Robotics Lab
1/12/2023 - 20/12/2024
Contact
Professor Stephan Chalup
University of Newcastle
School of Information and Physical Sciences
stephan.chalup@newcastle.edu.au
Research Collaborations
The map is a representation of a researchers co-authorship with collaborators across the globe. The map displays the number of publications against a country, where there is at least one co-author based in that country. Data is sourced from the University of Newcastle research publication management system (NURO) and may not fully represent the authors complete body of work.
Country | Count of Publications | |
---|---|---|
Australia | 139 | |
Germany | 7 | |
Ireland | 4 | |
New Zealand | 4 | |
China | 3 | |
More... |
News
News • 13 Nov 2020
University of Newcastle secures over $6 million in ARC funding
The Australian Research Council (ARC) has awarded the University of Newcastle more than $6 million in competitive research funding through its Discovery Projects and Linkage Projects schemes.
News • 7 Jun 2018
Team of teen soccer robots represent Australia at World Cup
A team of teen robots, dubbed NUbots, are set to represent Australia at the RoboCup soccer world championships in Montréal.
Professor Stephan Chalup
Position
Professor
Interdisciplinary Machine Learning Research Group
School of Information and Physical Sciences
College of Engineering, Science and Environment
Focus area
Data Science and Statistics
Contact Details
stephan.chalup@newcastle.edu.au | |
Phone | (02) 492 16080 |
Fax | (02) 492 16929 |
Links |
Personal webpage ResearchGate Research Networks Google+ |
Office
Room | ES227 |
---|---|
Building | Engineering Science Building |
Location | Callaghan University Drive Callaghan, NSW 2308 Australia |