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Wei-Min (Weimin) Shen

Director, Polymorphic Robotics Laboratory 
Associate Director, USC Center for Robotics and Embedded Systems 
Project Leader, Information Sciences Institute
Research Associate Professor, Computer Science Department
    
USC Information Sciences Institute
4676 Admiralty Way, Marina del Rey, CA 90292
Email: "shen at isi.edu"
Phone: (310) 448-8710, Fax: (310) 822-0751

Dr. Wei-Min (Weimin) Shen is the Director of Polymorphic Robotics Laboratory, the Associate Director of the Center for Robotics and Embedded Systems, and a Research Associate Professor in Computer Science at University of Southern California. He received his Ph.D. under Nobel Laureate Professor Herbert A. Simon and co-advisor Professor Jaime Carbonell from Carnegie Mellon University in 1989. His thesis is titled Autonomous Learning from the Environment Based on Percepts and Actions. Dr. Shen has over 25 years of research experience and his current research interests include self-reconfigurable and metamorphic systems, autonomous robots, Machine Learning, Artificial Intelligence, and Life Science. He has over 100 publications in these areas. He is the recipient of a Silver-Medal Award in 1996 AAAI Robotics Competition, a World Championship Award in 1997 Middle-sized RoboCup Competition, a Meritorious Service Award at ISI in 1997, and a Phi Kappa Phi Faculty Recognition Award at USC in 2003. He is the author of Autonomous Learning from Environment (W.H.Freeman), a 360-page book on how machines learn from their environment based on "surprises". He is the inventor of SuperBot, a co-inventor of CONRO, and the inventor of hormone-inspired distributed and decentralized control for self-reconfigurable systems (US Patent #006636781). He has served as chairs and committee members for international conferences and workshops in Robotics, Machine Learning, and Data Mining, and as editorial board members for scientific books and research journals. His research activities have been reported by leading scientific journals such as SCIENCE (9/26/1997 and 8/8/2003) and NATURE (5/28/2004), and media press such as CNN, PBS, Discovery, and other newspapers and magazines in the world. His research has been supported by NSF, AFOSR, DARPA, ARO, and NASA. He is the conference program chair for the 7th International Conference on Autonomous Intelligent Systems, and has served on the program committee for AAAI, AAMAS, KDD, ICRA, IROS, and other international technical conferences.


Dr. Shen's research is focused on Self-Reconfigurable, Adaptive, and Autonomous Robots and other Artificial Intelligent Systems. He is currently the PI for the SuperBot project that builds modular, multifunctional and self-reconfigurable robots for space exploration. His past projects include: the PI for SOLAR, a project for self-assembly in space; the Co-PI for CONRO, a project for self-reconfigurable robots; the PI for SOALA, a project investigates how robots adapt to a new environment by exploration; the PI for DataCrystal, a project for Data Mining; the Co-PI for KOJAK, a project for Link Discovery; the Co-PI for DYNAMITE, a project for distributed task optimizatioin; the PI for Adpateam, a project for adaptive agent team structures; the PI for DreamTeam, a RoboCup97 championship robot team, and the PI for YODA, an award-wining indoor navigation robot at AAAI96 Robot competition. He is the inventor of Digital Hormones for biologically inspired distributed control for any self-reconfigurable systems, agents, robots, and networks.

Dr. Shen is the chair for Self-Reconfigurable Robots Workshop at RSS-2005 at MIT, the chair for Self-Reconfigurable Robots Workshop at ICRA 2001, the co-chair for the 7th International Conference on Intelligent and Autonomous Systems (IAS-7) in 2002, the editorial member for Handbook of Knowledge Discovery and Data Mining (Cambridge University Press) 2000, and the guest editor for the Special Issue on Self-Reconfigurable Robots for IEEE Transactions on Mechatronics.

For more information, please visit his Polymorphic Robotics Lab. For CS561 in 2013 Fall, please click Here.

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