A/Prof. Stephan Chalup
|Work Phone||(02) 492 16080|
|Fax||(02) 492 16929|
School of Elect Engineering and Computer Science
The University of Newcastle, Australia
|Office||ES227, Engineering Science|
Stephan K. Chalup is an Associate Professor in Computer Science and Software Engineering at the University of Newcastle, Australia. He received his Ph.D. in Computer Science (Machine Learning) from Queensland University of Technology in Brisbane. He spent his undergraduate years in Germany at the University of Konstanz and later completed a Diploma in Mathematics with Biology (~Masters by Research) at the University of Heidelberg.
He is the leader of the Newcastle Robotics Laboratory and of the Interdisciplinary Machine Learning Research Group (IMLRG). His research interests include autonomous agents, computer vision, dimensionality reduction, human centered computing, machine learning, and neural information processing systems. He has published over 70 articles and received research grants with a total value of over a million dollars. He is a member of the ACM, the ACS and a senior member of the IEEE.
- PhD, Queensland University of Technology, 2001
- Diplom in Mathematiker (equiv Degree), University of Heidelberg
- Autonomous Robots
- Computational Intelligence
- Data Mining
- Dimensionality Reduction and Kernel Methods
- Machine Learning
- Medical Image Analysis
- Neural Information Processing
- Vision and Image Processing
The Interdisciplinary Machine Learning Research Group (IMLRG) and the Newcastle Robotics Laboratory have the common objective to advance research in the area of Anthropocentric Biocybernetic Computing. It investigates the complex interactions between humans and their environment on all levels including the cell-, circuit-, and body-levels and the ecosystem. When applied to real-world computing and autonomous agents the aim is to develop systems that approximate human-like skills on tasks such as vision processing, facial expression analysis, space representation, and human-robot interaction. Machine learning techniques are employed for fine tuning the parameters of general models until they perform at extraordinary levels of skill on selected tasks. Biologically motivated models are complemented by alternative designs. The strategy is to approximate human-level skills in artificial systems from several different directions, that is, through interdisciplinary projects in collaboration with experts from relevant disciplines (e.g. electrical engineering, architecture, neuroscience, and applied mathematics). Associated projects involve computer vision, data mining, machine learning, pattern recognition, time series analysis, and intelligent system design. Our special interest is on applications of kernel machines and more specifically on methods for non-linear dimensionality reduction or manifold learning.
Karlsruhe Institute of Technology (KIT), Germany, Institute AIFB.
Fields of Research
|080100||Artificial Intelligence And Image Processing||60|
Centres and Groups
- Hunter Medical Research Institute
- PRC - Priority Research Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine
- Applied Informatics Research Group (AIR)
- Hunter Medical Research Institute - Information Based Medicine Program
Body relevant to professional practice.
- Member - Senior Member of the IEEE
- Member - Australian Computer Society (ACS)
- Editor - Central European Journal of Computer Science
- Member - International Journal of Advanced Robotic Systems
RoboCup World Champion
RoboCup Federation (China)
First place for the NUManoid robot soccer team in the Standard Platform League
RoboCup World Champion
RoboCup Federation (Germany)
First place for the NUbot robot soccer team in the Four Legged League.
Held various administrative responsibilities including: Robotics lab coordinator, leader of the IMLRG research group, seminar coordinator, marketing coordinator, examinations officer, Computer Science Honours coordinator 2/2006, 2011, 2013, BE(software) programme convenor 2007, and Student Academic Conduct Officer (SACO) 2010-2012.
- Computer Graphics
- Computer Vision
- Machine Intelligence
- Machine Learning
Full-time lecturer since 2001. Taught courses in machine intelligence, computer graphics, computer linguistics, computer vision, internet communications, biocomputation and advanced machine learning.