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Evolutionary Computing at Work: Opportunities and Challenges
发布时间:2016-10-30     浏览量:   分享到:

 

讲座题目: Evolutionary Computing at Work: Opportunities and Challenges

讲座人  Kay Chen Tan 教授

讲座时间09:00-10:00

讲座日期: 2016-10-30

地点   长安校区 beat365正版唯一官网报告厅 

主办单位:beat365正版唯一官网 生物大数据计算科研团队

讲座内容简介:

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.

讲座人简介:

Dr. Tan Kay Chen received the B. Eng. degree with First Class Honors in Electronics and Electrical Engineering, and the Ph.D. degree from the University of Glasgow, Scotland, in 1994 and 1997, respectively. He is actively pursuing research in computational and artificial intelligence, with applications to multi-objective optimization, scheduling, automation, data mining, and games.

Dr. Tan has published over 100 journal papers, over 100 papers in conference proceedings, co-authored 5 books including Multiobjective Evolutionary Algorithms and Applications (Springer-Verlag, 2005), Modern Industrial Automation Software Design (John Wiley, 2006; Chinese Edition, 2008), Evolutionary Robotics: From Algorithms to Implementations (World Scientific, 2006; Review), Neural Networks: Computational Models and Applications (Springer-Verlag, 2007), and Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms (Springer-Verlag, 2009), co-edited 4 books including Recent Advances in Simulated Evolution and Learning (World Scientific, 2004), Evolutionary Scheduling (Springer-Verlag, 2007), Multiobjective Memetic Algorithms (Springer-Verlag, 2009), and Design and Control of Intelligent Robotic Systems (Springer-Verlag, 2009).

Dr. Tan has been an Invited Keynote/Plenary speaker for over 40 international conferences. He served in the international program committee for over 100 conferences and involved in the organizing committee for over 50 international conferences, including the General Co-Chair for IEEE Congress on Evolutionary Computation 2007 in Singapore. Dr. Tan is 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 the Editor-in-Chief of IEEE Transactions on Evolutionary Computation. He was the Editor-in-Chief of IEEE Computational Intelligence Magazine (2010-2013). He 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.

Dr. Tan is a Fellow of IEEE. He is the awardee of the 2012 IEEE Computational Intelligence Society (CIS) Outstanding Early Career Award for his contributions to evolutionary computation in multiobjective optimization. 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. He was also a winner of the NUS Outstanding Educator Awards (2004), the Engineering Educator Awards (2002, 2003, 2005, 2014), the Annual Teaching Excellence Awards (2002, 2003, 2004, 2005, 2006), the Honour Roll Awards (2007), and a Fellow of the NUS Teaching Academic (2009-2012).