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【專題演講】國際科技人士:筑波大學prof. Sakurai 蒞校主講,歡迎參加

主題:【科技部邀請訪問演講】國際科技人士:筑波大學prof. Sakurai

講題:Eigen-analysis Engine for Large-scale Simulation and Data Analysis

日期:2017/12/28  星期四 13:00~14:00  




Large-scale eigenvalue problems arise in a wide variety of scientific and engineering applications such as nano-scale materials simulation, vibration analysis of automobile components, data clustering, etc.

Principal components analysis (PCA) and spectral clustering are well-known examples of the application of eigenvalue problems. In this talk, we introduce the Sakurai-Sugiura method (SSM) for large-scale eigenvalue problems. Based on this method, we are developing a high-performance analysis engine for simulation and data analysis. Recently, we are also developing a high-performance algorithm for deep neural networks. Some numerical examples illustrate properties of our methods.


Tetsuya Sakurai is a Professor of Department of Computer Science, and the Director of Center for Artificial Intelligence Research (C-AIR) at the University of Tsukuba. He is also a visiting professor at the Open University of Japan, and a visiting researcher of Advanced Institute of Computational Science at RIKEN. He also serves as the CEO of MathDesign, LLC. During 2014-2016 he was the Director of Office for Strategies of R&D, and from 2011 to 2015 he was the Dean of College of Information Science at the University of Tsukuba. He received a Ph.D. in Computer Engineering from Nagoya University in 1992. His primary research interests are in the field of computational mathematics and numerical algorithms. Specifically, he is interested in high performance computing algorithms for large-scale computer simulations. He also develops algorithms for big data analysis, image analysis, and neural network computations. He leads a CREST project of Japan Science and Technology Agency (JST) which is focused on the development of high performance scientific software for next-generation supercomputers. He is a member of the Japan Society for Industrial and Applied Mathematics (JSIAM), the Mathematical Society of Japan (MSJ), Information Processing Society of Japan (IPSJ), Society for Industrial and Applied Mathematics (SIAM).


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