Dr Alexandre Mendes
Senior Lecturer
School of Information and Physical Sciences (Computing and Information Technology)
- Email:alexandre.mendes@newcastle.edu.au
- Phone:(02) 4921 6172
The disruptive nature of smart technology
A researcher of international standing, Dr Alexandre Mendes is using machine learning to solve real-world problems, helping to revolutionise decisions, processes and even diagnoses.
Artificial intelligence (AI) is often touted as the future of technology. But what exactly is AI and why is it so exciting for businesses, industries and governments alike?
Dr Alexandre Mendes’ research focuses on the AI area of machine learning, which is when computer systems identify data patterns, learn from data and solve problems with minimal human involvement.
Machine learning is driving new technological advancements every day across almost every industry. It is helping diseases be identified earlier, driving new ecommerce solutions and facilitating novel voice search applications. Over his career, Alexandre has utilised machine learning for a range of practical outcomes. Most recently, his work is exploring how deep learning and optimisation—two areas of machine learning—can improve the efficiency of Australia’s transport and energy industries.
“My work focuses on artificial intelligence, but that is a huge research area. More specifically, I work in the two sub-areas of optimisation and deep learning.
“Optimisation involves the use of software to solve complex problems that require decision making. Deep learning involves the use of deep neural networks, which mimic the structure of the brain, for complex classification and prediction problems.
“The use of these complex computational tools impacts so many different areas. We have so much local knowledge, so much potential, and so much room for improvement that the opportunities are endless.”
On track to success
Central to machine learning is optimisation. This complex process is essentially about finding the best solutions to a problem by analysing data, switching tactics when needed and minimising errors. In partnership with the Hunter Region rail network, Alexandre is researching how this clever technique can be applied to coal train logistics.
“I am currently working with train logistics, helping to push as many trains through a rail network as physically possible, without violating operational and safety constraints.
“That is a very difficult problem because most of the network consists of single tracks. Therefore, trains travelling in opposite directions must negotiate who will stop at the few available side tracks so the other trains can pass through. When you are trying to push as many trains as possible through the system, this coordination becomes critical.”
Alexandre’s high-level goal is to create a method that can schedule train trips in real time through the rail network. This will help to get the best performance out of the existing infrastructure—boosting efficiency while keeping costs at a minimum.
“Better train coordination affects everyone. The same knowledge used for coal train coordination in the Hunter Region can be used for better coordination in, say, the Sydney Metro, or the intercity trains. But more short term, having a more efficient supply chain for coal export in Newcastle generates more revenue and jobs.”
Powering the future
Another aspect of Alexandre’s work involves researching the practical applications of deep learning. Part of machine learning, this process allows computers to self-learn using data examples.
Teaming up with CSIRO’s Newcastle energy centre, Alexandre is using this deep learning process to predict solar energy output. The AI technology analyses extensive reams of cloud cover images and weather information, such as wind speed and direction, then, based on this data, learns how to predict short-term solar generation.
“Humans are very good at guessing the configuration of the clouds in the sky in the future, after just a few seconds observing how they move. But for computers, that is still a very difficult task.”
Alexandre explains that determining how much sunlight will reach a solar farm within a few minutes is crucial for better coordination between highly variable renewable generation and more stable base generation based on coal and gas.
“Solar generation prediction will help maintain power supply quality and better integrate renewables into the generation mix. The high-level goal is to predict how much energy a solar farm will produce in, say, the next 20 minutes, so that the transmission/distribution network can adjust beforehand for the variation in generation.
“This research will affect anyone with a solar panel on their roof who wants to integrate their excess generation with the grid, and the companies that run the system.”
Smart, industry-focused solutions
Alexandre’s research is always conducted in collaboration with industry partners, allowing results to translate into immediate solutions.
“By working directly with companies, any positive result from our research can be applied immediately and influence how business is conducted in organisations.
“It can be challenging sometimes to generate enough interest and confidence from industry, so that companies want to invest in this kind of applied research. But once they do, they realise the immense potential that the research has to offer their business.”
The highly applicable nature of machine learning across industries has put Alexandre and his team in hot demand. They are always keen to take on new PhD students to help with the work, and find inspiration in helping the next generation test new disruptive technologies that could facilitate better processes and outcomes for people.
“The sheer amount of research that is generated by the School of Electrical Engineering and Computing means we are always looking for PhD students with a computer science or software engineering background. Having students conducting research in such areas also means that they can see the results of their work being used immediately.
“Personally, it is great to see students grow throughout the process and finish their PhD as motivated, competent researchers that, in many cases, end up being employed by the partner company to continue the research work internally.
“At the University of Newcastle, we are committed to producing the highly skilled workforce that the world needs so much in this era of constant innovation and incredibly fast technology change.”
The disruptive nature of smart technology
A researcher of international standing, Dr Alexandre Mendes is using machine learning to solve real-world problems, helping to revolutionise decisions, processes and even diagnoses.Artificial intelligence (AI) is often touted as the future of technology. But what exactly is AI and…
Career Summary
Biography
My research interests are concentrated in Machine Learning and Optimisation. The applications have been in the following areas:
- Machine Scheduling (Single, Parallel, Flowshop, Jobshop)
- Energy distribution planning
- Oil transportation planning
- Coal chain logistics
- Robotics (especially computer vision and deep neural networks)
- Data classification of medical conditions
Research Expertise
I have co-authored a total of 86 publications, including book chapters, journals and conferences articles. My publications have been cited over 1,900 times (Google Scholar). I have also been awarded, as co-chief investigator, 15 research grants and direct industry research funding from the Australian Research Council (ARC), CSIRO, Hunter Valley Coal Chain Coordinator, Cisco Systems Australia, Energy Australia, the Hunter Medical Research Institute (HMRI), the Brazilian Government, and from The University of Newcastle, totalling just above AU$ 1.5 million.
I am a reviewer of several international journals, including Annals of Mathematics and Artificial Intelligence, IEEE Transactions on Power Systems, Memetic Computing, International Journal of Production Economics, Computers and Industrial Engineering, IEEE Transactions on Systems, Man, and Cybernetics - Part C, Optimization Letters, European Journal of Industrial Engineering, Production Planning & Control, Computers and Operations Research, among others.
I am also a reviewer 'of international standing' for the Australian Research Council (ARC): Discovery projects (since 2006), Laureate Fellowships (2009), Future Fellowships (2012-2013), DECRA projects (2012, 2017), Linkage projects (2013-2014).
Teaching Expertise
I have been lecturing since semester 1, 2008. My courses are in C++, Matlab, Data Structures, Software Development, Software Architecture and Work Integrated Learning. Those courses are targeted at students from Computer Science, Software Engineering, Information Technology and several other Engineering programs.
In 2009, I completed the Graduate Certificate in the Practice of Tertiary Teaching, through the Centre for Teaching and Learning, after taking the following courses: TEHE6010 - Principles and Practice of University Teaching and Learning, TEHE6020 - Course Design, TEHE6030 - Assessment of Student Learning, TEHE6040 - Supervision and Mentoring
Administrative Expertise
Administrative responsibilities within the Discipline of Computing and Information Technology include:
- Deputy Head of School Marketing and Outreach (Jul 2021 - Aug 2023)
- Computer Science Program Convenor (since 2nd sem, 2019)
- Head of Discipline (Jul 2013 - Dec 2016)
- Work Integrated Learning and Outreach Coordinator (since Jul 2016)
- Acting Computer Science Honours Coordinator (2nd sem, 2012; 1st sem, 2016)
- NUbots Deputy Team Leader (since Oct 2011)
- Marketing Coordinator (Jun 2011 - Dec 2016)
- Seminar Coordinator (Jan 2005 - Dec 2012)
- Help Desk Coordinator (Mar 2011 - Dec 2012)
Qualifications
- PhD (Electrical Engineering), Universidade Estadual de Campinas - Brazil
- Bachelor in Applied Mathematics, Universidade Estadual de Campinas - Brazil
- Master of Engineering (Electrical), Universidade Estadual de Campinas - Brazil
- Graduate Certificate Practice of Tertiary Teaching, University of Newcastle
Keywords
- Combinatorial optimisation
- Computer vision
- Evolutionary algorithms
- Robotics
Languages
- Portuguese (Mother)
- Spanish (Working)
- English (Fluent)
Fields of Research
Code | Description | Percentage |
---|---|---|
460203 | Evolutionary computation | 30 |
490304 | Optimisation | 40 |
461104 | Neural networks | 30 |
Professional Experience
UON Appointment
Title | Organisation / Department |
---|---|
Senior Lecturer | University of Newcastle School of Electrical Engineering and Computing Australia |
Academic appointment
Dates | Title | Organisation / Department |
---|---|---|
1/9/2007 - 1/12/2011 | Lecturer | University of Newcastle School of Electrical Engineering and Computing Australia |
1/9/2003 - 1/9/2007 | Research Academic | University of Newcastle Engineering & Built Environment Australia |
Awards
Award
Year | Award |
---|---|
2020 |
Work Integrated Learning Staff Member of the Year The University of Newcastle |
Recipient
Year | Award |
---|---|
2012 |
Best student paper award - A Novel Approach to Ball Detection for Humanoid Robot Soccer 25th Australasian Joint Conference on Artificial Intelligence (Australia) |
2003 |
Best paper award - Applying Memetic Algorithms to the Analysis of Microarray Data EvoBIO2003 - 1st European Workshop on Evolutionary Bioinformatics (United Kingdom) |
Research Award
Year | Award |
---|---|
2011 |
Pro Vice-Chancellor's Award for Research Excellence Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Book (6 outputs)
Year | Citation | Altmetrics | Link | |||||
---|---|---|---|---|---|---|---|---|
2018 |
11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9-11, 2018, Proceedings, Part 1, Springer, Switzerland (2018)
|
|||||||
2018 |
11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9-11, 2018, Proceedings, Part 2, Springer, Switzerland (2018)
|
|||||||
2018 |
Chen Z, Mendes A, Yan Y, Chen S, Preface (2018)
|
|||||||
Show 3 more books |
Chapter (6 outputs)
Year | Citation | Altmetrics | Link | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
2017 |
Mathieson L, Mendes A, Marsden J, Pond J, Moscato P, 'Computer-aided breast cancer diagnosis with optimal feature sets: Reduction rules and optimization techniques', Bioinformatics, Springer Nature, New York, NY 299-325 (2017) [B1]
|
Nova | |||||||||
2008 |
Mendes ADS, Scott R, Moscato PA, 'Microarrays - Identifying molecular portraits in prostrate tumors with different gleason patterns', Clinical Bioinformatics, Humana Press, New York 131-151 (2008) [B1]
|
Nova | |||||||||
2008 |
Hourani MA, Berretta RE, Mendes ADS, Moscato PA, 'Genetic signatures for a rodent model of Parkinson's disease using combinatorial optimization methods', Bioinformatics, Humana Press, New York 379-392 (2008) [B1]
|
||||||||||
2004 |
Moscato PA, Cotta C, Mendes ADS, 'Memetic Algorithms', Studies in fuzziness and soft computing - new optimization techniques in engineering, Springer, New York Not Known (2004) [B1]
|
||||||||||
2004 |
Moscato PA, Mendes ADS, Linhares A, 'VLSI design: gate matrix layout problem', Studies in fuzziness and soft computing - new optimization techniques in engineering, Springer, New York Not Known (2004) [B1]
|
||||||||||
2004 |
Moscato PA, Mendes ADS, Cotta C, 'Scheduling and production & control: MA', Studies in fuzziness and soft computing - new optimization techniques in engineering, Springer, New York Not Known (2004) [B1]
|
||||||||||
Show 3 more chapters |
Journal article (26 outputs)
Year | Citation | Altmetrics | Link | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
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]
|
Nova | |||||||||
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]
|
||||||||||
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]
|
Nova | |||||||||
2019 |
Rocha de Paula M, Boland N, Ernst AT, Mendes A, Savelsbergh M, 'Throughput optimisation in a coal export system with multiple terminals and shared resources', Computers and Industrial Engineering, 134 37-51 (2019) [C1]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
2016 |
Fenn S, Mendes A, Budden DM, 'Addressing the non-functional requirements of computer vision systems: a case study', Machine Vision and Applications, 27 77-86 (2016) [C1]
|
Nova | |||||||||
2015 |
Isbister GK, Maduwage K, Saiao A, Buckley NA, Jayamanne SF, Seyed S, et al., 'Population pharmacokinetics of an Indian F(ab')2 snake antivenom in patients with Russell's viper (Daboia russelii) bites', PLoS Neglected Tropical Diseases, 9 1-13 (2015) [C1]
|
Nova | |||||||||
2015 |
Flannery M, Budden DM, Mendes A, 'FlexDM: Simple, parallel and fault-tolerant data mining using WEKA.', Source code for biology and medicine, 10 13 (2015) [C1]
|
Nova | |||||||||
2014 |
Mendes A, Cardoso RL, Mário PC, Martinez AL, Ferreira FR, 'Insolvency Prediction in the Presence of Data Inconsistencies', Intelligent Systems in Accounting, Finance and Management, 21 155-167 (2014) [C1]
|
Nova | |||||||||
2013 |
Mendes A, Boland N, Guiney P, Riveros C, 'Switch and Tap-Changer Reconfiguration of Distribution Networks Using Evolutionary Algorithms', IEEE TRANSACTIONS ON POWER SYSTEMS, 28 85-92 (2013) [C1]
|
Nova | |||||||||
2012 |
Ravetti MG, Riveros RC, Mendes ADS, Resende MGC, Pardalos PM, 'Parallel hybrid heuristics for the permutation flow shop problem', Annals of Operations Research, 199 269-284 (2012) [C1]
|
Nova | |||||||||
2012 |
Linhares A, Freitas AETA, Mendes ADS, Jarbas S, 'Entanglement of perception and reasoning in the combinatorial game of chess: Differential errors of strategic reconstruction', Cognitive Systems Research, 13 72-86 (2012) [C1]
|
Nova | |||||||||
2009 |
Rosso OA, Mendes ADS, Rostas JA, Hunter M, Moscato PA, 'Distinguishing childhood absence epilepsy patients from controls by the analysis of their background brain electrical activity', Journal of Neuroscience Methods, 177 461-468 (2009) [C1]
|
Nova | |||||||||
2009 |
Rosso OA, Mendes ADS, Berretta RE, Rostas JA, Hunter M, Moscato PA, 'Distinguishing childhood absence epilepsy patients from controls by the analysis of their background brain electrical activity (II): A combinatorial optimization approach for electrode selection', Journal of Neuroscience Methods, 181 257-267 (2009) [C1]
|
Nova | |||||||||
2009 |
Ikin A, Riveros RC, Moscato PA, Mendes ADS, 'The Gene Interaction Miner: A new tool for data mining contextual information for protein-protein interaction analysis', Bioinformatics, 26 283-284 (2009) [C1]
|
Nova | |||||||||
2007 |
Berretta RE, Mendes ADS, Moscato PA, 'Selection of discriminative genes in microarray experiments using mathematical programming', Journal of Research and Practice in Information Technology, 39 287-299 (2007) [C1]
|
Nova | |||||||||
2007 |
Moscato PA, Mendes ADS, Berretta RE, 'Benchmarking a Memetic Algorithm for Ordering Microarray Data', Biosystems, 88 56-75 (2007) [C1]
|
||||||||||
2005 |
Franca PM, Gupta JND, Mendes ADS, Moscato PA, Veltink KJ, 'Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups', Computers & Industrial Engineering, 48 491-506 (2005) [C1]
|
Nova | |||||||||
2005 |
Mendes ADS, Franca PM, Lyra C, Pissarra C, Cavellucci C, 'Capacitor placement in large-sized radial distribution networks', IEE Proceedings-Generation Transmission and Distribution, 152 496-502 (2005) [C1]
|
Nova | |||||||||
2004 |
Mendes ADS, Linhares A, 'A multiple-population evolutionary approach to gate matrix layout', International journal of systems science, 35 13-23 (2004) [C1]
|
||||||||||
2002 |
Mendes AS, Muller FM, Franca PM, Moscato P, 'Comparing meta-heuristic approaches for parallel machine scheduling problems', PRODUCTION PLANNING & CONTROL, 13 143-154 (2002)
|
||||||||||
2002 |
Mendes AS, Franca PM, Moscato P, 'Fitness landscapes for the total tardiness single machine scheduling problem', Neural Network World, 12 165-180 (2002) This paper addresses several issues related to the approximate solution of the Single Machine Scheduling problem with sequence-dependent setup times using metaheuristic methods. I... [more] This paper addresses several issues related to the approximate solution of the Single Machine Scheduling problem with sequence-dependent setup times using metaheuristic methods. Instances with known optimal solution are solved using a memetic algorithm and a multiple start approach. A fitness landscape analysis is also conducted on a subset of instances to understand the behavior of the two approaches during the optimization process. We also present a novel way to create instances with known optimal solutions from the optimally solved asymmetric travelling salesman problem (ATSP) instances. Finally we argue for the test set of instances to be used in future works as a convenient performance benchmark.
|
||||||||||
2001 |
Franca PM, Mendes A, Moscato P, 'A memetic algorithm for the total tardiness single machine scheduling problem', EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 132 224-242 (2001)
|
||||||||||
1998 |
Teixeira E, Mendes A, 'An extension of the model for the problem of workpiece scheduling in a flexible manufacturing cell', PRODUCTION PLANNING & CONTROL, 9 176-180 (1998)
|
||||||||||
Show 23 more journal articles |
Conference (49 outputs)
Year | Citation | Altmetrics | Link | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
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)
|
||||||||||
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]
|
Nova | |||||||||
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]
|
||||||||||
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.
|
||||||||||
2021 |
Chen S, Berretta R, Mendes A, Clark A, 'Integrating Shelf Life Constraints in Capacitated Lot Sizing and Scheduling for Perishable Products', Proceedings of the ASOR/DORS Conference 2018, Melbourne, Australia (2021) [E1]
|
Nova | |||||||||
2020 |
Amos M, Middleton R, Biddulph A, Mendes A, 'Implementation and analysis of dynamic stability for bipedal robotic motion', 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia (2020) [E1]
|
Nova | |||||||||
2020 |
Sanhueza C, Mendes A, Jackson M, Clement R, 'An efficient genetic algorithm for the train scheduling problem with fleet management', 2020 IEEE Congress on Evolutionary Computation (CEC), Glasgow, United Kingdom (2020) [E1]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
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]
|
Nova | |||||||||
2017 |
Mendes ADS, Jackson M, Rocha de Paula M, Rojas O, 'Iterative train scheduling in networks with tree topologies: a case study for the Hunter Valley Coal Chain', Proceedings of the 22nd International Congress on Modelling and Simulation, Hobart, Australia (2017) [E1]
|
Nova | |||||||||
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]
|
Nova | |||||||||
2015 |
Isbister GK, Maduwage K, Saiao A, Buckley NA, Jayamanne SF, Seyed S, et al., 'Population pharmacokinetics of an Indian F(ab')2 snake antivenom in patients with Russell's viper bite', CLINICAL TOXICOLOGY (2015) [E3]
|
||||||||||
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]
|
Nova | |||||||||
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.
|
Nova | |||||||||
2014 |
Annable B, Budden D, Mendes A, 'NUbugger: A visual real-time robot debugging system', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2014) [E1] As modern autonomous robots have improved in their ability to demonstrate human-like motor skills and reasoning, the size and complexity of software systems have increased proport... [more] As modern autonomous robots have improved in their ability to demonstrate human-like motor skills and reasoning, the size and complexity of software systems have increased proportionally, with developers actively working to leverage the full processing performance of next-generation computational hardware. This software complexity corresponds with increased difficulty in debugging low-level coding issues, with the traditional methodology of inferring such issues from emergent high-level behaviour rapidly approaching intractability. This paper details the development and functionality of NUbugger: a visual, real-time and open source robot debugging utility that provides the user with comprehensive information regarding low-level functionality. This represents a paradigm shift from corrective to preventative debugging, and concrete examples of the application of NUbugger to the identification of fundamental implementation errors are described. The system implementation facilitates simple and rapid extension or modification, making it a useful utility for debugging any similar complex robotic framework. © 2014 Springer-Verlag Berlin Heidelberg.
|
Nova | |||||||||
2014 |
Budden D, Mendes A, 'Unsupervised recognition of salient colour for real-time image processing', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2014) [E1] Humans have the subconscious ability to create simple abstractions from observations of their physical environment. The ability to consider the colour of an object in terms of &qu... [more] Humans have the subconscious ability to create simple abstractions from observations of their physical environment. The ability to consider the colour of an object in terms of "red" or "blue", rather than spatial distributions of reflected light wavelengths, is vital in processing and communicating information about important features within our local environment. The real-time identification of such features in image processing necessitates the software implementation of such a process; segmenting an image into regions of salient colour, and in doing so reducing the information stored and processed from 3-dimensional pixel values to a simple colour class label. This paper details a method by which colour segmentation may be performed offline and stored in a static look-up table, allowing for constant time dimensionality reduction in an arbitrary environment of coloured features. The machine learning framework requires no human supervision, and its performance is evaluated in terms of feature classification performance within a RoboCup robot soccer environment. The developed system is demonstrated to yield an 8% improvement over slower traditional methods of manual colour mapping. © 2014 Springer-Verlag Berlin Heidelberg.
|
Nova | |||||||||
2013 |
Budden D, Walker J, Flannery M, Mendes ADS, 'Probabilistic Gradient Ascent with Applications to Bipedal Robotic Locomotion', Australasian Conference on Robotics and Automation, Sydney, Australia (2013) [E1]
|
Nova | |||||||||
2013 |
Boland NL, McGowan B, Mendes A, Rigterink F, 'Modelling the Capacity of the Hunter Valley Coal Chain to Support Capacity Alignment of Maintenance Activities', MODSIM2013, Proceedings of the 20th International Congress on Modelling and Simulation, Adelaide, SA (2013) [E1]
|
Nova | |||||||||
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]
|
Nova | |||||||||
2012 |
Budden DM, Fenn SK, Walker JR, Mendes ADS, 'A novel approach to ball detection for humanoid robot soccer', AI 2012: Advances in Artificial Intelligence. 25th Australasian Joint Conference Proceedings, Sydney, Australia (2012) [E1]
|
Nova | |||||||||
2011 | Cardoso RL, Mendes ADS, Mario PDC, Martinez AL, Ferreira FR, 'Accounting information inconsistencies and their effects on insolvency prediction models', Abstracts. 34th Annual Congress of the European Accounting Association, Rome, Italy (2011) [E1] | Nova | |||||||||
2011 |
Mendes ADS, 'Identification of breast cancer subtypes using multiple gene expression microarray datasets', AI 2011: Advances in Artificial Intelligence 24th Australasian Joint Conference Perth, Australia, December 5-8, 2011 Proceedings, Perth, WA (2011) [E1]
|
Nova | |||||||||
2011 |
Mendes ADS, Boland NL, 'Multi-objective optimisation of power restoration in electricity distribution systems', AI 2011: Advances in Artificial Intelligence 24th Australasian Joint Conference Perth, Australia, December 5-8, 2011 Proceedings, Perth, WA (2011) [E1]
|
Nova | |||||||||
2010 |
Mendes ADS, Boland NL, Guiney P, Riveros RC, '(N-1) contingency planning in radial distribution networks using genetic algorithms', 2010 IEEE/PES Transmission and Distribution. Proceedings, San Paulo, Brazil (2010) [E1]
|
Nova | |||||||||
2008 |
Mendes ADS, 'Consensus clustering of gene expression microarray data using genetic algorithms', PRIB 2008 Supplementary Proceedings, Melbourne, VIC (2008) [E1]
|
Nova | |||||||||
2007 |
Hourani MA, Mendes ADS, Berretta RE, Moscato PA, 'Genetic biomarkers for brain hemisphere differentiation in Parkinson's Disease', Computational Models for Life Sciences (CMLS '07): 2007 International Symposium. Conference Proceedings, Gold Coast, QLD (2007) [E1]
|
Nova | |||||||||
2007 |
Tuga M, Berretta RE, Mendes ADS, 'A hybrid simulated annealing with kempe chain neighborhood for the university timetabling problem', Proceedings of the 6th IEEE/ACIS International Conference on Computer and Information Science, Melbourne (2007) [E1]
|
Nova | |||||||||
2007 |
Inostroza-Ponta M, Mendes ADS, Berretta RE, Moscato PA, 'An integrated QAP-based approach to visualize patterns of gene expression similarity', Progress in Artificial Life, Gold Coast, QLD (2007) [E1]
|
Nova | |||||||||
2006 |
Garcia VJ, Franca PM, Mendes ADS, Moscato PA, 'A Parallel Memetic Algorithm Applied to the Total Tardiness Machine Scheduling Problem', IPDPS 2006, 20th International Parallel and Distributed Processing Symposium, 2006, Rhodes Island, Greece (2006) [E1]
|
Nova | |||||||||
2006 |
Inostroza-Ponta M, Berretta RE, Mendes ADS, Moscato PA, 'An automatic graph layout procedure to visualize correlated data', Artificial Intelligence in Theory and Practice, Santiago, Chile (2006) [E1]
|
Nova | |||||||||
2005 |
Berretta RE, Mendes ADS, Moscato PA, 'Integer Programming Models and Algorithms for Molecular Classification of Cancer from Microarray Data', Proceedings of the twenty eighth Australasian Computer Science Conference (ACSC 2005) Newcastle, Australia, January, 2005, Newcastle, N.S.W (2005) [E1]
|
Nova | |||||||||
2005 |
Moscato PA, Mathieson L, Mendes ADS, Berretta RE, 'The Electronic Primaries: Predicting the U.S. Presidency Using Feature Selection with Safe Data Reduction', Proceedings of the twenty eighth Australasian Computer Science Conference (ACSC 2005) Newcastle, Australia, January, 2005, Newcastle, N.S.W (2005) [E1]
|
Nova | |||||||||
2005 |
Moscato PA, Berretta RE, Hourani MA, Mendes ADS, Cotta C, 'Genes related with Alzheimer's disease: A comparison of evolutionary search, statistical and integer programming approaches', Applications on Evolutionary Computing: EvoWorkkshops 2005: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, and EvoSTOC, Lausanne, Switzerland (2005) [E1]
|
Nova | |||||||||
2005 |
Berretta RE, Cotta C, Hourani MA, Mendes ADS, Moscato PA, 'Hacia una Mejor Compresion del Perfil Genetico de la Enfermedad de Alzheimer a Traves de Metaheuristicas', Proceedings of the MAEB2005, Granada, Spain (2005) [E2]
|
||||||||||
2005 |
Mendes ADS, Cotta C, Garcia V, Franca P, Moscato PA, 'Gene Ordering in Microarray Data Using Parallel Memetic Algorithms', International Conference Workshops on Parallel Processing, 2005. ICPP 2005 Workshops, Oslo, Norway (2005) [E1]
|
||||||||||
2005 |
Moscato PA, Berretta RE, Mendes ADS, 'A New Memetic Algorithm for Ordering Datasets: Applications in Microarray Analysis', Proceedings of MIC2005, Vienna, Austria (2005) [E2]
|
||||||||||
2003 |
Cotta C, Mendes A, Garcia V, Franca P, Moscato PA, 'Applying memetic algorithms to the analysis of microarray data', Applications of Evolutionay Computing: EvpWorkshops 2003, EvoBIO, EvoCOP, EvoIASP, EvoMUSART, EvoROB and EvoSTIM: Proceedings, Essex, UK (2003) [E1]
|
||||||||||
2002 |
Mendes A, Franca P, Moscato PA, Garcia V, 'Population Studies for the Gate Matrix Layout Problem', Lecture Notes in Computer Science, Berlin (2002) [C1]
|
||||||||||
2000 |
Silva AC, Ohishi T, Mendes AS, Franga FA, Delgado EAR, 'Using genetic algorithm and simplex method to stabilize an oil treatment plant inlet flow', Proceedings of the Biennial International Pipeline Conference, IPC (2000) This paper presents a hybrid approach, composed of a genetic algorithm and a linear programming method, to achieve an efficient pipeline network operation. The pipeline network op... [more] This paper presents a hybrid approach, composed of a genetic algorithm and a linear programming method, to achieve an efficient pipeline network operation. The pipeline network optimization consists of the determination of pump scheduling over a short-Term horizon, usually one or more days ahead. The resulting mathematical problem has a dynamic and combinatorial characteristic, in which a sub-optimal solution was obtained through these two mathematical tools in a short computational time. The approach was applied in a Pipeline Network to a study case based on the Patagonia Argentina, which is comprised of 16 tanks and linked pumps, with 66 kilometers of pipelines, that transport the production of more than 100 wells to a pre-processing plant. The goal was to obtain a constant input flow rate at the plant respecting physical and chemical processes requirements.
|
||||||||||
Show 46 more conferences |
Grants and Funding
Summary
Number of grants | 23 |
---|---|
Total funding | $1,616,910 |
Click on a grant title below to expand the full details for that specific grant.
20232 grants / $80,000
To validate the current technology offering and then seek to create new developments and optimise the functionality of the Wayfinder product$50,000
Funding body: Design Anthology Pty Limited
Funding body | Design Anthology Pty Limited |
---|---|
Project Team | Doctor Rukshan Athauda, Doctor Alexandre Mendes, Mr Harris Saleem, Doctor Alexandre Mendes, Mr Josh Jeffress, Doctor Alexandre Mendes |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Investigator |
Funding Start | 2023 |
Funding Finish | 2023 |
GNo | G2300706 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
GGWP Personality Alignment Project$30,000
Funding body: Good Game Well Played Pty Ltd
Funding body | Good Game Well Played Pty Ltd |
---|---|
Project Team | Doctor Alexandre Mendes, Ms Jacquie Garrett, Mr Ethan Laity |
Scheme | University of Newcastle Industry Training and Engagement (UNITE) Internship |
Role | Lead |
Funding Start | 2023 |
Funding Finish | 2023 |
GNo | G2300917 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
20212 grants / $115,000
Medibus: a platform for remote health services delivery$100,000
Funding body: Cisco Systems Australia Pty Ltd
Funding body | Cisco Systems Australia Pty Ltd |
---|---|
Project Team | Doctor Alexandre Mendes, Conjoint Professor Chris Levi, James Stewart |
Scheme | Research Grant |
Role | Lead |
Funding Start | 2021 |
Funding Finish | 2021 |
GNo | G2100686 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
RoboCup Junior Hunter Region 2022$15,000
Funding body: Kirby Foundation
Funding body | Kirby Foundation |
---|---|
Project Team | Aaron Wong |
Scheme | External Donation |
Role | Lead |
Funding Start | 2021 |
Funding Finish | 2022 |
GNo | |
Type Of Funding | C3120 - Aust Philanthropy |
Category | 3120 |
UON | N |
20182 grants / $99,426
Design and implementation of an optimisation algorithm for the scheduling of coal trains$49,713
Funding body: Hunter Valley Coal Chain Coordinator Limited
Funding body | Hunter Valley Coal Chain Coordinator Limited |
---|---|
Project Team | Doctor Alexandre Mendes |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2018 |
Funding Finish | 2018 |
GNo | G1800735 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Design and implementation of an optimisation algorithm for the scheduling of coal trains$49,713
Funding body: Department of Industry, Innovation and Science
Funding body | Department of Industry, Innovation and Science |
---|---|
Project Team | Doctor Alexandre Mendes |
Scheme | Entrepreneurs' Programme: Innovation Connections |
Role | Lead |
Funding Start | 2018 |
Funding Finish | 2018 |
GNo | G1800828 |
Type Of Funding | C2100 - Aust Commonwealth – Own Purpose |
Category | 2100 |
UON | Y |
20176 grants / $219,429
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 | Lead |
Funding Start | 2017 |
Funding Finish | 2020 |
GNo | G1700966 |
Type Of Funding | C2100 - Aust Commonwealth – Own Purpose |
Category | 2100 |
UON | Y |
Computational techniques for coal supply chain$45,000
Funding body: Hunter Valley Coal Chain Coordinator Limited
Funding body | Hunter Valley Coal Chain Coordinator Limited |
---|---|
Project Team | Doctor Alexandre Mendes, Dr Mateus Rocha de Paula, Mr Allan Messeder Caldas Bretas |
Scheme | Post Graduate Scholarship |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | G1701318 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Data sampling in wireless networks: applications and tools integration$24,000
Funding body: FAPEAL - Alagoas State Research Foundation
Funding body | FAPEAL - Alagoas State Research Foundation |
---|---|
Project Team | Andre Aquino, Alexandre Mendes and 5 others |
Scheme | UNIVERSAL |
Role | Investigator |
Funding Start | 2017 |
Funding Finish | 2018 |
GNo | |
Type Of Funding | International - Competitive |
Category | 3IFA |
UON | N |
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 | Investigator |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | G1700582 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
Predicting agglomerate distribution using evolutionary optimisation techniques$10,402
Funding body: Faculty of Engineering and Built Environment - The University of Newcastle (Australia)
Funding body | Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
---|---|
Project Team | Alexandre Mendes and Roberto Moreno-Atanasio |
Scheme | FEBE Strategic Pilot Grant |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
22nd International Congress on Modelling and Simulation$1,500
Funding body: Faculty of Engineering and Built Environment - The University of Newcastle (Australia)
Funding body | Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
---|---|
Project Team | Alexandre Mendes |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20151 grants / $5,000
Image processing techniques for the automatic identification of available places in unstructured parking lots$5,000
Funding body: Faculty of Engineering and Built Environment - The University of Newcastle (Australia)
Funding body | Faculty of Engineering and Built Environment - The University of Newcastle (Australia) |
---|---|
Project Team | Alexandre Mendes and Stephan Chalup |
Scheme | FEBE Strategic Pilot Grant |
Role | Lead |
Funding Start | 2015 |
Funding Finish | 2015 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20122 grants / $101,490
Smart-CPMAT: Configuring intelligent buildings with wireless sensor networks$100,000
Funding body: FAPEAL - Alagoas State Research Foundation
Funding body | FAPEAL - Alagoas State Research Foundation |
---|---|
Project Team | Andre Aquino, Alexandre Mendes and 15 others |
Scheme | Universal |
Role | Investigator |
Funding Start | 2012 |
Funding Finish | 2016 |
GNo | |
Type Of Funding | International - Competitive |
Category | 3IFA |
UON | N |
The 25th Australasian Joint Conference on Artificial Intelligence, Sydney, 4-7 December 2012$1,490
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Project Team | Doctor Alexandre Mendes |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2012 |
Funding Finish | 2012 |
GNo | G1201047 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20114 grants / $951,500
Mathematics and Computing for Integrated Stockyard-centric Management of Mining Supply Chains$560,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Doctor Thomas Kalinowski, Conjoint Professor Natashia Boland, Professor Peter Stuckey, Doctor Alexandre Mendes, Doctor Faramroze Engineer, Professor Martin Savelsbergh, Dr Andreas Ernst |
Scheme | Linkage Projects |
Role | Investigator |
Funding Start | 2011 |
Funding Finish | 2014 |
GNo | G1000957 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Mathematics and Computing for Integrated Stockyard-centric Management of Mining Supply Chains$260,000
Funding body: Hunter Valley Coal Chain Coordinator Limited
Funding body | Hunter Valley Coal Chain Coordinator Limited |
---|---|
Project Team | Conjoint Professor Natashia Boland, Professor Peter Stuckey, Doctor Alexandre Mendes, Doctor Faramroze Engineer, Professor Martin Savelsbergh, Dr Andreas Ernst, Doctor Thomas Kalinowski |
Scheme | Linkage Projects Partner Funding |
Role | Investigator |
Funding Start | 2011 |
Funding Finish | 2013 |
GNo | G1001065 |
Type Of Funding | Grant - Aust Non Government |
Category | 3AFG |
UON | Y |
Mathematics and Computing for Integrated Stockyard-centric Management of Mining Supply Chains$130,000
Funding body: Triple Point Australia
Funding body | Triple Point Australia |
---|---|
Project Team | Conjoint Professor Natashia Boland, Professor Peter Stuckey, Doctor Alexandre Mendes, Doctor Faramroze Engineer, Professor Martin Savelsbergh, Dr Andreas Ernst, Doctor Thomas Kalinowski |
Scheme | Linkage Projects Partner Funding |
Role | Investigator |
Funding Start | 2011 |
Funding Finish | 2013 |
GNo | G1001080 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
24th Australasian Joint Conference on Artificial Intelligence, Perth, Australia, 5 - 8 December 2011$1,500
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Project Team | Doctor Alexandre Mendes |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2011 |
Funding Finish | 2012 |
GNo | G1100923 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20091 grants / $20,000
Optimal Switching Strategies to maintain Load Balancing in No-Failure/Minimum-Impact Outage Scenarios$20,000
Funding body: Ausgrid
Funding body | Ausgrid |
---|---|
Project Team | Doctor Alexandre Mendes, Conjoint Professor Natashia Boland |
Scheme | Sponsorship Agreement |
Role | Lead |
Funding Start | 2009 |
Funding Finish | 2010 |
GNo | G0900080 |
Type Of Funding | Other Public Sector - State |
Category | 2OPS |
UON | Y |
20081 grants / $5,000
Consensus clustering of samples using gene expresssion microarray data$5,000
Funding body: University of Newcastle - Faculty of Engineering & Built Environment
Funding body | University of Newcastle - Faculty of Engineering & Built Environment |
---|---|
Project Team | Doctor Alexandre Mendes |
Scheme | Pilot Grant |
Role | Lead |
Funding Start | 2008 |
Funding Finish | 2008 |
GNo | G0189055 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20062 grants / $20,065
Computational Methods for Breast Cancer Genetic Profiling Using Genome-Wide Data$15,000
Funding body: Hunter Medical Research Institute
Funding body | Hunter Medical Research Institute |
---|---|
Project Team | Doctor Alexandre Mendes, Doctor Pritha Mahata |
Scheme | Special Competitive Research Fund for Early Career Researchers in Cancer |
Role | Lead |
Funding Start | 2006 |
Funding Finish | 2006 |
GNo | G0185931 |
Type Of Funding | Not Known |
Category | UNKN |
UON | Y |
A New Web Data Mining Tool for Functional Genomics Analysis$5,065
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Scheme | Independent Investigator Project Grant Scheme |
Role | Lead |
Funding Start | 2006 |
Funding Finish | 2006 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
Research Supervision
Number of supervisions
Current Supervision
Commenced | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2022 | PhD | Zero-Shot Learning for Environmental Audio | 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 | Co-Supervisor |
Past Supervision
Year | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
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 | Principal 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 | Principal 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 | Principal Supervisor |
2022 | PhD | Lot-sizing and Scheduling Optimization in Food Supply Chain | PhD (Computer Science), 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 | Co-Supervisor |
2020 | PhD | Target Curricula for Multi-Target Classification: The Role of Internal Meta-Features in Machine Teaching | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Co-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 | Co-Supervisor |
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 | 65 | |
Brazil | 14 | |
United States | 4 | |
Argentina | 3 | |
China | 3 | |
More... |
Dr Alexandre Mendes
Position
Senior Lecturer
School of Information and Physical Sciences
College of Engineering, Science and Environment
Focus area
Computing and Information Technology
Contact Details
alexandre.mendes@newcastle.edu.au | |
Phone | (02) 4921 6172 |
Mobile | 0403064885 |
Fax | (02) 4921 6929 |
Links |
Research Networks Research Networks |
Office
Room | ES236 |
---|---|
Building | Engineering Science - D.W. George. |
Location | Callaghan University Drive Callaghan, NSW 2308 Australia |