Keynote Speakers for LSMS & ICSEE 2014
Plenary Lecture 1
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Xue, Yusheng
Honorary President of State Grid Electric Power Research
Institute (SGEPRI or NARI), China |
Professor Yusheng Xue received MSc degree in Electrical Engineering from EPRI, China in 1981 and PhD degree from the University of Liege, Belgium in 1987. He was elected an academician of Chinese Academy of Engineering in 1995. He is now the Honorary President of State Grid Electric Power Research Institute (SGEPRI or NARI), China. He holds the positions of Adjunct Professor in many universities in China and a conjoint professor of the University of Newcastle in Australia. He was also an honorary professor of the University of Queensland, Australia. He is the Editor-in-Chief of the Journal of "Automation of Electric Power System" (in Chinese) and that of the "Journal of Modern Power System and Clean energy" (in English), and a member of Editorial Board of IET Generation, Transmission & Distribution, and Chairman of Technical Committee of Chinese National Committee of CIGRE since 2005.
Plenary Lecture 2
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Yeung, Daniel S.
Chair Professor at South China University of Technology, China |
Daniel
S. Yeung
(Ph.D., M.Sc., M.B.A., M.S., M.A., B.A.) has worked as an Assistant Professor at
Rochester Institute of Technology, New York, as Principal Lecturer and Associate
Head of the Computer Science Department at City University of Hong Kong, as head
of the Management Information Department, as Department Head and Chair Professor
of the Department of Computing, The Hong Kong Polytechnic University, Hong Kong.
Currently he is a Chair Professor at South China University of Technology,
China.
He also held industrial and business positions as a Technical Specialist/Application Software Group Leader at the Computer Consoles, Inc., Rochester, New York, an Information Resource Sub-manager/Staff Engineer at the Military and Avionics Division, TRW Inc., San Diego, California, and an Information Scientist of the Information System Operation Lab, General Electric Corporate Research and Development Centre, Schenectady, New York.
His current research interests include neural-network sensitivity analysis, pattern recognition, and fuzzy rough set.
Plenary Lecture 3
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Pedrycz, Witold
Department of Electrical & Computer Engineering From Numeric Models to Granular System Modeling |
Abstract: In the era of advanced methodologies and practices of system modeling, we are faced with ever growing challenges of building models of complex systems that are in full rapport with reality. These challenges are multifaceted. Human centricity becomes of paramount relevance in system modeling and because of this models need to be customized and easily interpretable. More and more visibly, experimental data and knowledge of varying quality being directly acquired from experts have to be efficiently utilized in the construction of models. The quality of data and ensuing quality of models has to be prudently quantified. There are ongoing and even exacerbated challenges to build intelligent systems, modeling multifaceted phenomena, and deliver efficient models that help users describe and understand systems and facilitate decision-making.
We have to become fully cognizant that processing and modeling has to be realized with the use of entities endowed with well-defined semantics, namely information granules. Human do not perceive reality and reason in terms of numbers but rather utilize more abstract constructs (information granules), which are helpful in setting up a certain cognitive perspective and ignore irrelevant details when dealing with the complexity of the systems.
In this talk, we introduce the key concepts of Granular Computing and demonstrate how this conceptual framework gives rise to human-centric system modeling and granular models. We discuss several representative formal setups used in describing and processing information granules including fuzzy sets, rough sets, and interval calculus. Key architectures of models dwell upon relationships among information granules. In particular, we elaborate on a principle of incompatibility in system modeling stressing a need for achieving a sound tradeoff between precision and relevance of a model, which is of particular relevance when coping with systems of high complexity. We also demonstrate how information granularity and its optimization can be regarded as an important design asset to be exploited in system modeling. With this regard, two categories of models along with their granular augmentations are studied in detail, namely rule-based models and neural networks.
Witold
Pedrycz
is a
Professor and Canada Research Chair (CRC) in Computational Intelligence in the
Department of Electrical and Computer Engineering, University of Alberta,
Edmonton, Canada. He is also with the Systems Research Institute of the Polish
Academy of Sciences, Warsaw, Poland. He also holds an appointment of special
professorship in the School of Computer Science, University of Nottingham, UK.
In 2009 Dr. Pedrycz was elected a foreign member of the Polish Academy of
Sciences. In 2012 he was elected a Fellow of the Royal Society of Canada. Witold
Pedrycz has been a member of numerous program committees of IEEE conferences in
the area of fuzzy sets and neurocomputing. In 2007 he received a prestigious
Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Council. He is
a recipient of the IEEE Canada Computer Engineering Medal 2008. In 2009 he has
received a Cajastur Prize for Soft Computing from the European Centre for Soft
Computing for "pioneering and multifaceted contributions to Granular Computing".
In 2013 has was awarded a Killam Prize. In the same year he received a Fuzzy
Pioneer Award 2013 from the IEEE Computational Intelligence Society.
His main research directions involve Computational Intelligence, fuzzy modeling
and Granular Computing, knowledge discovery and data mining, fuzzy control,
pattern recognition, knowledge-based neural networks, relational computing, and
Software Engineering. He has published numerous papers in this area. He is also
an author of 15 research monographs covering various aspects of Computational
Intelligence, data mining, and Software Engineering.
Dr. Pedrycz is intensively involved in editorial activities. He is an
Editor-in-Chief of Information Sciences, Editor-in-Chief of IEEE Transactions on
Systems, Man, and Cybernetics Systems and Editor-in-Chief of WIREs Data Mining
and Knowledge Discovery (Wiley). He currently serves as an Associate Editor of
IEEE Transactions on Fuzzy Systems and is a member of a number of editorial
boards of other international journals.
Plenary Lecture 4
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Pardalos, Panos M.
Distinguished Professor Data Mining and Optimization for Large and Massive Datasets in Biomedical Applications |
Abstract: In recent years, data mining, optimization algorithms and heuristic methods have been increasingly used for the analysis of large and massive datasets for a wide variety of biomedical applications. Such applications include fMRI, EEG, Raman spectroscopy, NMR, and patient databases. These datasets are often classified as having very high dimensionality, and typically consist of relatively small sample sizes, while other datasets may have large sample numbers yet low dimensionality. The proper implementation and combination of techniques such as machine learning, global optimization, clustering, and dimensionality reduction is necessary for accurate analysis of these large and massive datasets. This analysis often provides useful information about the internal structure of the data sets they represent. In this talk, I will discuss our group's work on several optimization and data mining computational approaches for biomedical applications.
Dr. Panos M. Pardalos serves as a Distinguished Professor of the Industrial and Systems Engineering Department and the J. Crayton Pruitt Family Department of Biomedical Engineering, and is also an affiliate faculty member of the Computer and Information Science Department, as well as the Hellenic Studies Center at the University of Florida Engineering.
He is also the Director of the Center for Applied Optimization (http://www.ise.ufl.edu/cao/). Dr. Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization, data mining, and massive computing for applications in telecommunications, e-commerce, and biomedical engineering. Professor Pardalos is a Fellow of AAAS and INFORMS. He is a member of several Academies of Sciences and holds several honorary professorships and Ph.D. degrees at universities around the world. Dr. Panos Pardalos, was recently awarded the 2013 EURO Gold Medal Prize, bestowed by the Association for European Operational Research Societies, as well as recipient of the 2013 Constantin Carathéodory Prize of the International Society of Global Optimization.
Plenary Lecture 5
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Huosheng Hu 1University of Essex, U.K. 2Shanghai University, China New Trends in Advanced Medical and Rehabilitation Robots |
Abstract: As the level of intelligence and robustness in robotics technologies advances and computers become more powerful, robots are gradually doing formerly human manual work in the operating theatre and hospitals. Currently, there are three new trends in advanced medical and rehabilitation robots. The 1st new trend is the application of surgical and implantable robots to improve consistency and reliability, promote minimum invasive for fast patient recovery, as well as reduce the time of surgery operations. The 2nd new trend is the application of wearable and assistive robots to support mobility and independent living of patients and elderly. The 3rd new trend is the use of network technology and tele-operated robots for home-based healthcare and rehabilitation at a reduced cost. This talk will focus on these trends and uncover what they tell us about the future of the field. Some successful systems are demonstrated via video clips.
Huosheng
Hu
is a Professor in the School of Computer Science & Electronic Engineering at the
University of Essex, leading the Robotics Group. His research interests include
behaviour-based robotics, human-robot interaction, service robots, embedded
systems, learning algorithms, mechatronics, and pervasive computing. He has
published over 430 papers in journals, books and conferences in these areas, and
received a number of best paper awards. Prof. Hu is a Fellow of Institute of
Engineering & Technology, a Fellow of Institute of Measurement & Control, a
senior member of IEEE and ACM, a founding member of IEEE Robotics & Automation
Society Technical committee on Networked Robots. He has been a Program Chair or
a member of Advisory/Organising Committee for many international conferences
such as IEEE IROS, ICRA, ICMA, ROBIO, ICIA, and IASTED RA and CA conferences.
Currently, He is Editor-in-Chief for International Journal of Automation and
Computing, Founding Editor-in-Chief for Online Robotics Journal and an Executive
Editor of International Journal of Mechatronics and Automation.
Plenary Lecture 6
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Umezu, Mitsuo Professor ,Faculty of Science & Engineering,Waseda University Director, Centerfor Advanced Biomedical Sciences,(TWIns), Waseda University Dept. Head, Cooperative Major in Advanced Biomedical Sciences, Joint Graduate School of Tokyo Women's Medical University and Waseda University Our new way to collaborate - Another EBM; Engineering Based Medicine |
visitor.