Xin-She Yang

Xin-She Yang, PhD
Department of Engineering
University of Cambridge, UK  

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Biography

Dr Xin-She Yang received his DPhil in Applied Mathematics from the University of Oxford, then worked at Leeds University and Cambridge University for a few years, and now is a Senior Research Scientist at National Physical Laboratory. Xin-She Yang is also a Distinguished Professor of Shaanxi Province at Xi'an Engineering University, and a Guest Professor at Shandong University and Harbin Engineering University. He has authored a dozen books with Wiley, World Scientific, Dunedin Academic and Springer, and published more than 110 papers.Xin-She Yang is the Editor-in-Chief of Int. J. Mathematical Modeling and Numerical Optimization (IJMMNO, Inderscience), serves as an editorial board member of several international journals, including Elsevier's Journal of Computational Science (JoCS), IJAI, SJI and IJBIC, and the editor of OCP Science book series. He is also vice chair of the IEEE CIS task force. Xin-She Yang is also an Honorary Fellow of Australia Institute of High Energetic Materials. In addition to his interests in mathematical modeling, computational mathematics and optimization, he is also enthusiastic about artificial intelligence and met heuristic algorithms, and thus have developed some nature-inspired algorithms such as Firefly Algorithm and Cuckoo Search. He is the recipient of 1996 Garside Scholar Award of Oxford University. He has been on program committees of over 25 international conferences such as ICCS'10, MIC'09, EA'09, Meta'10, BIOMA'10, ICAART'10, and WCE'10, and acted as program co-chair of COMS'10, COMS'11 and ITBI'10. His research on cuckoo search has been highlighted in the media, including Science Daily (May 2010) and Scientific Computing (June 2010). Xin-She Yang has given many invited talks at over a dozen universities

Research Interest

Dr Xin-She Yang  major research interests focus on Applied Mathematics and Mathematical Modeling,Computational Mathematics,Engineering Design, Optimization,Nature-Inspired Algorithms,Swarm Intelligence and Metaheuristics.