Wang Lipo

Biography

Wang Lipo received the BS degree from National University of Defense Technology, China, and the PhD degree from Louisiana State University, USA. In 1989, he was a postdoctoral fellow at Stanford University, USA. In 1990, he was a faculty member in the Department of Electrical Engineering, University College, ADFA, University of New South Wales, Australia. From 1991 to 1993 he was on the staff of the Laboratory of Adaptive Systems, National Institutes of Health, USA. From 1994 to 1997 he was a tenured faculty member at Deakin University, Australia. Since 1998, he has been Associate Professor at the School of EEE, NTU. He has published 200 papers in journals and conferences. He holds a U.S. patent in neural networks. He has authored 2 monographs and edited 20 books. His work has been cited 400 times in the ISI Web of Science by other researchers. He was keynote/plenary speaker for several international conferences. He is Associate Editor for IEEE Transactions on Neural Networks (since 2002), IEEE Transactions on Evolutionary Computation (since 2003), and IEEE Transactions on Knowledge and Data Engineering (since 2005). He is Area Editor of the Soft Computing journal (since 2002). He serves on the Editorial Board of 8 additional international journals. He was Vice President for Technical Activities (2006-2007) and Chair of the Emergent Technologies Technical Committee (2004-2005), IEEE Computational Intelligence Society. He has been on the Governing Board of the Asia-Pacific Neural Network Assembly (APNNA) since 1999 and served as APNNA President in 2002/2003. He won the 2007 APNNA Excellent Service Award. He was Founding Chair of both the IEEE Engineering in Medicine and Biology Chapter Singapore and IEEE Computational Intelligence Chapter Singapore. He serves/served as General/Program/Steering Committee Chair for 15 international conferences and as Member of steering/advisory/organizing/program committees of over 150 international conferences.

Research Interest

Nature-inspired computation, including neural networks, evolutionary computation, fuzzy systems, and chaos, with applications to data mining, bioinformatics, and combinatorial optimization.