报告题目: EC AT WORK: OPPORTUNITIES AND CHALLENGES
报告时间：2016年10月31日上午10:00至11:00
报告地点：南一楼中311
邀请方：“多谱信息处理技术”国家级重点实验室
Abstract: Evolutionary Computing (EC), which is based on the principles of natural selection and genetic inheritance, is often considered a global optimization methodology with a metaheuristic or stochastic optimization character. It is distinguished by the use of a population of candidate solutions rather than traditional approach of iterating over a single point in the search space. EC is being increasingly applied to many problems, ranging from practical applications in industry to cutting-edge scientific research. The plenary will provide a brief overview of this exciting research field including opportunities and challenges faced in applying EC to a variety of real-world multi-objective problems, such as design automation, robust optimization and logistic application. In particular, a case study involving the estimation of remaining useful life (RUL) for turbofan engines in the area of robust prognostic will be studied. As one of the key enablers of condition-based maintenance, prognostic involves the core task of determining the RUL of the system. The plenary will also present an application of evolutionary deep learning ensembles to improve the prediction accuracy of RUL estimation for turbofan engines.
Bio:DrKay Chen Tan received the B.Eng. (Hons.) degree in electronics and electrical engineering and the Ph.D. degree from University of Glasgow, Glasgow, U.K., in 1994 and 1997, respectively. He is currently with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. He is actively pursuing research in computational intelligence, with applications to multi-objective optimization, scheduling, data analytics, prognostics, BCI etc.
Dr Tan has published over 250 journal and conference papers and co-authored 5 books. He has been an Invited Keynote/Plenary speaker for over 50 international conferences. He was the General Co-Chair for IEEE Congress on Evolutionary Computation 2007 in Singapore and the General Co-Chair for IEEE World Congress on Computational Intelligence 2016 in Vancouver, Canada. Dr Tan is currently an elected member of AdCom (2014-2016) and is an IEEE Distinguished Lecturer of IEEE Computational Intelligence Society (2011-2013; 2015-2017).
Dr Tan is a Fellow of IEEE. He is also the Editor-in-Chief of IEEE Transactions on Evolutionary Computation. He served as the Editor-in-Chief of IEEE Computational Intelligence Magazine (2010-2013), and currently serves as an Associate Editor / Editorial Board member of over 20 international journals, such as IEEE Transactions on Cybernetics, IEEE Transactions on Computational Intelligence and AI in Games, Evolutionary Computation (MIT Press), European Journal of Operational Research, Neural Computing and Applications, Journal of Scheduling, International Journal of Systems Science, etc.
He is the awardee of the 2012 IEEE Computational Intelligence Society (CIS) Outstanding Early Career Award for his contributions to evolutionary computation in multi-objective optimization. He also received the 2016 IEEE CIS Outstanding TNNLS Paper Award for his paper titled "Rapid Feedforward Computation by Temporal Encoding and Learning with Spiking Neurons". He also received the Recognition Award (2008) from the International Network for Engineering Education & Research (iNEER) for his outstanding contributions to engineering education and research. He was felicitated by the International Neural Network Society (INNS) India Regional Chapter (2014) for his outstanding contributions in the field of computational intelligence.
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