1994: Graduated from the Faculty of Engineering, Kyoto University|
1998: Received Ph.D. in Engineering from Kyoto University
1998: Researcher, Electrotechnical Laboratory, Tsukuba
2000: Visiting Researcher, GMD FIRST, Germany
2001: Researcher, AIST Computational Biology Research Center
2003-2004, 2006-2008: Senior Researcher, Max Planck Institute for Biological Cybernetics, Germany
2009: Senior Researcher, AIST Computational Biology Research Center
2014: Professor, University of Tokyo
Undergraduate: Biological Data Mining|
Graduate school: Advanced Biological Data Mining
In the beginning of my career, I studied machine learning theory and proposed several methods including the kernel subspace method, the TOP kernel and marginalized kernels . I then proposed matrix exponentiated gradient update for online learning  and conducted research on structured data such as graphs and trees . Recently, I have developed methods for detecting and testing combinatorial causes from large scale data .|
1) K. Tsuda et al., Marginalized kernels for biological sequences, Bioinformatics, 18(Suppl. 1):S268–S275, 2002.
2) K. Tsuda et al., A new discriminative kernel from probabilistic models. Neural Computation, 14(10):2397–2414, 2002.
3) K. Tsuda et al., Matrix exponentiated gradient updates for online learning and Bregman projection, Journal of Machine Learning Research, 6:995–1018, 2005.
4) H. Saigo et al., gBoost: A mathematical programming approach to graph classification and regression, Machine Learning, 75:69-89, 2009.
5) A. Terada et al., Statistical significance of combinatorial regulations, PNAS, 110(32):12996-13001, 2013.
Institute of Electronics, Information and Communication Engineers of Japan (IEICE)|
Information Processing Society of Japan (IPSJ)
Japanese Society for Bioinformatics (JSBI)
In future, I would like to develop novel data analysis algorithms that eventually lead to great scientific discoveries.|
|Messages to Students|
In many fields of science, computational algorithms and machine learning methods are indispensable. I hope many of you join us because there are lots of opportunities for young people.|