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Symposium 2004

SMA 4th Annual Symposium 2004

Workshop on Adaptive Computing

The Singapore-MIT Alliance Computer Science program is embarking on a research program focusing of the area of adaptive computing with emphasis on the application areas of distance education and distance healthcare.

In distance education specifically, and any distance interaction in general, our goal is to make the experience in many ways preferable to that of face-to-face interaction. Movies have become preferable to live theater (at least judging by box-office receipts) but not by attempting to be high-fidelity ``distance theater'' but rather by exploiting the characteristics of the new medium to provide a novel experience that cannot be duplicated in live theater. We propose to achieve such a transformation of the distance interaction experience by taking advantage of the exponentially decreasing cost of processing power, memory, bandwidth and cameras. As an example, these trends will soon make it feasible and cost effective to have arrays of cameras and microphones recording and transmitting an event such as a lecture. Access to these data streams on an individual's computer will allow personalized control of the viewing experience. These controls include being able to select different parts of the same scene for viewing, being able to reconstruct blocked views and being able to have instant replays if a critical part of the interaction is missed. These controls are useful for viewing a lecture on a blackboard and become particularly compelling for viewing demonstrations such as a surgery. In addition to that, the recorded streams are stored for future offline access.

In a healthcare environment, there is a network of sensors monitoring the condition of the patient. The information from these various sources needs to be integrated to be presented to the physician who is present. When the physician is not present, automated decisions need to be made to alert the medical staff or to administer emergency treatment when necessary. These same problems are present in distant monitoring of patients who are using wearable devices at home or in their daily lives.

Current attempts at distance interaction can be a frustrating rather than compelling experience. Configuration of the devices so that interaction is possible requires highly skilled technicians. Even if properly configured, changes in the network conditions often mean that reconfiguration is required in the middle of the interaction. On the systems level, we will be focusing on methods to develop an adaptive system that can automatically make the best use of available resources. On the applications level, distance interaction and monitoring is currently unnatural and sometimes ineffective. Making distance interaction and monitoring effective, natural and compelling requires the use of techniques from computer vision, artificial intelligence, graphics and signal processing.

The aim of the workshop is to:

Inform participants from industry and academia of the current and anticipated developments in the technologies relevant to distance interaction.
Explore requirements of the distance interaction domain from industry and users of such systems in order to formulate appropriate future research questions.

If you are interested in attending the workshop, please register at

https://www-appn.comp.nus.edu.sg/~eventreg/smasymp

by 12 January 2004. Attendance is free but space is limited.

Panelists Biodata

Charles E. Leiserson
Charles E. Leiserson received the B.S. degree in computer science and mathematics from Yale University, New Haven, Connecticut, in 1975 and the Ph.D. degree in computer science from Carnegie Mellon University, Pittsburgh, Pennsylvania, in 1981. In 1981, he joined the faculty of the Massachusetts Institute of Technology, Cambridge, Massachusetts. He is now Professor of Computer Science and Engineering in the MIT Department of Electrical Engineering and Computer Science and member of the Theory of Computation research group in the MIT Laboratory for Computer Science. He holds an Adjunct Professorship at the National University of Singapore and the positions of Director of System Architecture, Director of Research, and Network Architect at Akamai Technologies, Inc. of Cambridge, Massachusetts. He is the Director of the Computer Science Program of the Singapore-MIT Alliance, a distance-education initiative in which students in Singapore take MIT classes.

Prof. Leiserson's research centers on developing theoretical principles of parallel and distributed computing, especially as they relate to engineering reality. Prof. Leiserson pioneered the development of VLSI theory and has written many papers on VLSI algorithms, graph layout, and computer-aided design. His contributions include the divide-and-conquer method of graph layout and the retiming method for optimizing digital circuitry. Prof. Leiserson has been a leader in the development of parallel computing. As a graduate student at Carnegie Mellon, he wrote the first paper on systolic architectures with his advisor H.T. Kung. While Corporate Fellow of Thinking Machines Corporation, he designed and led the implementation of the network architecture for the Connection Machine Model CM-5 Supercomputer, which incorporates the fat-tree interconnection network he developed at MIT. He has designed and engineered many parallel algorithms, including ones for matrix linear algebra, graph algorithms, optimization, and sorting.

Prof. Leiserson's recent research has focused on dynamic, asynchronous parallel computing. His Cilk multithreaded language features a provably good work-stealing scheduler that guarantees the efficient execution of user programs. He and his research group designed and implemented the StarTech, *Socrates, and Cilkchess parallel chess-playing programs, which have won numerous prizes in international competition. A team of Cilk programmers led by Prof. Leiserson won First Prize in the 1998 ICFP Programming Contest sponsored by the International Conference on Functional Programming, in which Cilk was declared to be ``the programming language of choice for discriminating hackers.'' His Cilk work also inspired the creation of efficiently implementable distributed-memory consistency models, as well as ``cache-oblivious'' algorithms which exploit available processor caches efficiently without any tuning of cache-dependent parameters.

Prof. Leiserson's academic work has won many awards. His Ph.D. dissertation, Area-Efficient VLSI Computation, which deals with the design of systolic systems and with the problem of determining the VLSI area of a graph, won the first ACM Doctoral Dissertation Award in 1981, as well as the Fannie and John Hertz Foundation Doctoral Thesis Award. In 1985 he received a Presidential Young Investigator Award from the National Science Foundation. Three of his papers have received awards from the IEEE International Conference on Parallel Processing. His textbook, Introduction to Algorithms, coauthored with Ronald L. Rivest and Thomas H. Cormen, was named Best 1990 Professional and Scholarly Book in Computer Science and Data Processing by the Association of American Publishers. The textbook, now in its second edition with an additional coauthor, Clifford Stein, is currently the leading textbook on computer algorithms.

Prof. Leiserson is a member of the ACM, IEEE, and SIAM. In 1995-6, he was Shaw Visiting Professor in the Department of Information Systems and Computer Science at the National University of Singapore. A dedicated teacher, Prof. Leiserson has directly supervised 20 Ph.D. students and over 50 master's and bachelor's students.

Leslie P. Kaelbling
Leslie Pack Kaelbling is Professor of Computer Science and Engineering and Research Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology. She has previously held positions at Brown University, the Artificial Intelligence Center of SRI International, and at Teleos Research. She received an A. B. in Philosophy in 1983 and a Ph. D. in Computer Science in 1990, both from Stanford University. Prof. Kaelbling has done substantial research on designing situated agents, mobile robotics, reinforcement learning, and decision-theoretic planning. In 2000, she founded the Journal of Machine Learning Research, a high quality journal that is both freely available electronically as well as published in archival form; she currently serves as editor-in-chief. Prof. Kaelbling is an NSF Presidential Faculty Fellow, a former member of the AAAI Executive Council, the 1997 recipient of the IJCAI Computers and Thought Award, a trustee of IJCAII and a fellow of the AAAI.

Lee Kang Hoe
Lee Kang Hoe is Associate Professor and Consultant at Department of Medicine, National University Hospital and Director of Medical Intensive Care Unit at NUH.

He obtained his medical degree from University of Cambridge, UK, completed his residency training in Cambridge and obtained the Membership of Royal College of Physicians (London) in 1990. He underwent Critical Care Medicine Fellowhip in Pittsburgh, USA and completed the European Diploma of Intensive Care in 1995. He has been a Fellow of the Academy of Medicine (Singapore) since 1996.

Leong Tze Yun
Leong, Tze-Yun is an Associate Professor of Computer Science at the School of Computing, National University of Singapore, where she directs the Medical Computing Laboratory and leads the multi-disciplinary Biomedical Decision Engineering Group. She is the Co-Chair of the MIT-Singapore Alliance Computer Science Program. She is also the Founder and Chairman of ReasonEdge Technologies Inc., a global company group that specializes in next generation decision management and business intelligence technologies.

Tze-Yun received her S.B., S.M., and Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT). Her research focuses on decision analytic technologies that integrating information from multiple, heterogeneous sources. She is particular interested in using both genomic and phenotypic data to improve diagnosis, treatment, and prognostic or outcome analysis in biomedicine and health care. Tze Yun works closely in collaboration with leading hospitals and universities in Singapore and in US. She also has extensive consulting and business experiences in decision support technologies and biomedical informatics. She is an Associate Editor of the International Journal of Artificial Intelligence in Medicine and serves on the Editorial Board of the Journal of Biomedical Informatics.

Tan Tiong Hok, Daniel
Daniel Tan is currently the Director, Centre for Educational Development, and Associate Professor, School of Electrical and Electronic Engineering at the Nanyang Technological University. He obtained his BSc from University of Aston, Birmingham, England. He subsequently achieved a PhD from the University of Manchester Institute of Science and Technology and a post-graduate Diploma in Teaching in Higher Education from the Nanyang Technological University. His research interests cover Internet and computer security; human factors and usability. He is involved in several projects on information warfare, encryption, authentication, intrusion detection systems and usability.

Assoc Prof Tan, as Director of the Centre for Educational Development at the Nanyang Technological University, led a team to develop and implement an e-learning campus eco-system. This environment, comprising a holistic approach towards system design, learning platform, server architecture, coupled with edUtorium, the staff development program and pedagogical design has resulted in a high immersive and adoption rate, by both staff and students.

SMA CS Posters

Poster session on work done in SMA Computer Science program in Singapore and MIT.