Year: 2018

Suri7-Tanigawa

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Shin-ichi Tanigawa
Shin-ichi Tanigawa

Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo
Associate Professor

7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 Eng. 6 Bldg. Room 340
Tel: 03-5841-6906, ext. 26906
Fax:

E-mail：tanigawa＠mist.i.u-tokyo.ac.jp

[Home Page]

 

Curriculum Vitae

Mar. 2005 Graduated from the Department of Architecture and Architectural Engineering, Faculty of Engineering, Kyoto University
Mar. 2007 Graduated from the Master Course of the Department of Architecture and Architectural Engineering, Graduate School of Engineering, Kyoto University
Mar. 2010 Graduated from the the Doctor Course of the Department of Architecture and Architectural Engineering, Graduate School of Engineering, Kyoto University
Apr. 2010 – May 2011 Postdoctoral Fellow of Japan Society for the Promotion of Science
Jun. 2011 – Mar. 2017 Assistant Professor, Research Institute for Mathematical Sciences, Kyoto University
Apr. 2017 – Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo

Research Themes

● Discrete and Computational Geometry
Design and analysis of algorithms for geometric problems in engineering. Topics of particular interest are: rigidity theory and geometric graph theory.  

● Discrete Algorithms
Design and analysis of algorithms for discrete optimization problems. Topics of particular interest are: graph algorithms and combinatorial optimization.

Selected Publications

Satoru Fujishige and Shin-ichi Tanigawa: Polynomial combinatorial algorithms for skew-bisubmodular function minimization, Mathematical Programming, to appear, 2017.

Shin-ichi Tanigawa: Singularity degree of the positive semidefinite matrix completion problem, SIAM Journal on Optimization, 27, 986–1009, 2017.

Bill Jackson, Tibor Jordan and Shin-ichi Tanigawa: Unique low rank completability of partially filled matrices, Journal of Combinatorial Theory, Series B, 121, 432-462, 2016.

Shin-ichi Tanigawa: Sufficient conditions for globally rigidity of graphs, Journal of Combinatorial Theory Series B, 113: 123–140, 2015.

Shin-ichi Tanigawa: Matroids of gain graphs in applied discrete geometry. Transactions of the American Mathematical Society, 367, 8597-8641, 2015.

 

 

System Information Second Laboratory

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System Information Second Laboratory – Brain science based on system theory: brain function recording, brain function control – Laboratory homepage →
Ayumu Matani
Ayumu Matani
Associate Professor		  
Brain function recording
For instance, I investigate whether or not humans still possess subconscious geomagnetic reception by EEG recording and behavioral experiments.
Brain function control
I try to control brain functions by attaching a negative impedance circuit on the scalp, so that it modulates the volume conduction of dendritic currents.

Lab 4. Hiromichi Nagao

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Hiromichi Nagao
Hiromichi Nagao

Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo
Associate Professor

1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032 Eat. 3 Bldg. Room 33
Tel: +81-3-5841-1766 (ext. 21766)
Fax:+81-3-5841-1766

E-mail： nagao@mist.t.u-tokyo.ac.jp

[Home Page]

Curriculum Vitae

Mar. 1995 Bachelor degree from Faculty of Science, Kyoto University
Mar. 1997 Master degree from Graduate School of Science, Kyoto University
Mar. 2002 Ph. D., Graduate School of Science, Kyoto University
Apr. 2002 Visiting Researcher, Japan Nuclear Cycle Development Institute
Mar. 2006 Researcher, Japan Agency for Marine-Earth Science and Technology
Jun. 2009 Project Researcher, The Institute of Statistical Mathematics
Dec. 2010 Project Associate Professor, The Institute of Statistical Mathematics
Sep. 2013 Associate Professor, Earthquake Research Institute, The University of Tokyo
Oct. 2013 Associate Professor, Graduate School of Information Science and Technology, The University of Tokyo

Research Themes

We could not prevent the damage from spreading caused by the Great East Japan Earthquake, which took place on March 11, 2011, despite the recent developments of global-scale real-time observational networks and large-scale numerical simulations based on high-performance computing.

In order to save as many human lives as possible from future great earthquakes, we are dedicating to accumulate comprehensive knowledge through integration of observation and simulation data related to earthquakes, tsunamis and seismic hazards based on statistical methodologies such as data assimilation.

1. Data Assimilation
Data assimilation is a computational technique to integrate numerical simulation models and observational/experimental data based on Bayesian statistics. Data assimilation provides simulation models that are possible to predict the future, sequentially estimating parameters involved in the simulation models and state vectors at every time step. Data assimilation was originally developed in meteorology and oceanology; for example, the weather forecasting absolutely shows results of data assimilation. We develop data assimilation techniques for the solid Earth science to investigate earthquakes and tsunamis.

2. Sequential Bayesian Filters and Four-Dimensional Variational Method
In data assimilation, an appropriate method is to be selected from various types of sequential Bayesian filters or four-dimensional variational method (4DVar) to compare predictions obtained by numerical simulations and observational data, considering the purpose and computational cost. We have been developing new algorithms of sequential Bayesian filters and 4DVar that are suitable for practical problems in the solid Earth science.

Selected papers

Sasaki, K., A. Yamanaka, S. Ito, and H. Nagao, Data assimilation for
phase-field models based on the ensemble Kalman filter, Computational
Materials Science, Vol. 141, pp. 141-152, doi:10.1016/j.commatsci.2017.09.025, 2018.
Ito, S., H. Nagao, T. Kasuya, and J. Inoue, Grain growth prediction
based on data assimilation by implementing 4DVar on multi-phase-field
model, Science and Technology of Advanced Materials, Vol. 18, Issue 1, pp. 857-869, doi:10.1080/14686996.2017.1378921, 2017.
Kano, M., H. Nagao, K. Nagata, S. Ito, S. Sakai, S. Nakagawa, M. Hori,
and N. Hirata, Seismic wavefield imaging of long-period ground motion
in the Tokyo Metropolitan area, Japan, J. Geophys. Res. Solid Earth, Vol. 122, doi:10.1002/2017JB014276, 2017.
Kano, M., H. Nagao, D. Ishikawa, S. Ito, S. Sakai, S. Nakagawa, M.
Hori, and N. Hirata, Seismic wavefield imaging based on the replica
exchange Monte Carlo method, Geophys. J. Int., Vol. 208, pp. 529-545, doi:10.1093/gji/ggw410, 2017.
Ito, S., H. Nagao, A. Yamanaka, Y. Tsukada, T. Koyama, M. Kano, and J.
Inoue, Data assimilation for massive autonomous systems based on a
second-order adjoint method, Phys. Rev. E, 94, 043307, doi:10.1103/PhysRevE.94.043307, 2016.

 

Lab. 4 Fumiyasu Komaki

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Fumiyasu Komaki
Fumiyasu Komaki

Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo
Professor

7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 Eng. 6 Bldg. Room 349
Tel: +81-3-5841-6941 (ext. 26941)
Fax:+81-3-5841-8592

E-mail： komaki@mist.i.u-tokyo.ac.jp

[Home Page]

Curriculum Vitae

Mar. 1987 Bachelor degree from Department of Mathematical Engineering and Instrumentation Physics, Faculty of Engineering, The University of Tokyo
Mar. 1989 Master degree from Department of Mathematical Engineering and Information Physics, Graduate School of Engineering, The University of Tokyo
Mar. 1992 Ph. D. from Department of Statistical Science, School of Mathematical and Physical Science, The Graduate University for Advanced Studies
Apr. 1992 Research Associate, Department of Mathematical Engineering and Information Physics, Faculty of Engineering, The University of Tokyo
Apr. 1995 Associate Professor, The Institute of Statistical Mathematics, Ministry of Education, Science and Culture
Oct. 1998 Associate Professor, Department of Mathematical Engineering and Information Physics, Graduate School of Engineering, The University of Tokyo
Apr. 2001 Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Aug. 2009 Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo

Research Themes

1. Theoretical Statistics
　Bayes theory, Prediction theory, Information geometry

2. Statistical Modeling
　Statistical models and data analysis in neuroscience and seismology.

Selected papers

Shibue, R. and Komaki, F. (2017). Firing rate estimation using infinite mixture models and its application to neural decoding,
Journal of Neurophysiology, vol. 118, 2902–29.
Yano, K. and Komaki, F. (2017). Asymptotically minimax prediction in infinite sequence models,
Electronic Journal of Statistics, vol. 11, 3165-3195.
Kojima, M. and Komaki, F. (2016). Relations between the conditional normalized maximum likelihood distributions and the latent information priors,
IEEE Transactions on Information Theory, vol. 62, pp. 539-553.
Matsuda, T. and Komaki, F. (2015). Singular value shrinkage priors for Bayesian prediction, Biometrika, vol. 102, pp. 843-854.

 

Tomonari Sei

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Tomonari Sei
Tomonari Sei

Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo
Professor

7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 Eng. 6 Bldg. Room 353
Tel:
Fax:

E-mail： sei@mist.t.u-tokyo.ac.jp

[Home Page]

Curriculum Vitae

Mar. 2000 Bachelor degree from Department of Mathematical Engineering and Information Physics, Faculty of Engineering, The University of Tokyo
Mar. 2002 Master degree from Department of Mathematical Engineering and Information Physics, Graduate School of Engineering, The University of Tokyo
Mar. 2005 Ph. D. from Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Apr. 2005 Assistant Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Apr. 2011 Lecturer, Department of Mathematics, Faculty of Science and Technology, Keio University
Apr. 2014 Associate Professor, Department of Mathematics, Faculty of Science and Technology, Keio University
Apr. 2015 Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Jun. 2021 Professor, Mathematics and Informatics Center, The University of Tokyo

Research Themes

I study theoretical aspects of statistics (mathematical statistics).

1. Computational algebraic statistics: application of the holonomic gradient method to statistics.
2. Statistical modeling of rare events and time series data.
3. Statistical methods using optimal transport maps.

Selected papers

Sei, T. and Kume, A. (2015). Calculating the normalizing constant of the Bingham distribution on the sphere using the holonomic gradient method, Statistics and Computing, 25 (2), 321-332.
Sei, T. (2014). Infinitely imbalanced binomial regression and deformed exponential families, Journal of Statistical Planning and Inference, 149, 116-124.
Rueschendorf, L. and Sei, T. (2012). On optimal stationary couplings between stationary processes, Electronic Journal of Probability, 17 (17), 1-20.
Nakayama H., Nishiyama K., Noro M., Ohara K., Sei, T., Takayama, N. and Takemura A. (2011). Holonomic gradient descent and its application to the Fisher-Bingham integral, Advances in Applied Mathematics, 47 (3), 639-658.

 

Mathematical Informatics 1st Laboratory

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Mathematical Cryptography Laboratory (Mathematical Informatics 1st Laboratory)
– Let’s study the foundation of information security. – 		HomePage of Lab.→
Tsuyoshi Takagi
Tsuyoshi Takagi
Professor		 Atsushi Takayasu
Atsushi Takayasu
Lecturer
Cryptography
Modern cryptography has become one of the most important research fields in information technology. We aim at development and security evaluation of the next-generation cryptographic systems. In particular, we study post-quantum
cryptography based on the mathematical problems (such as coding theory, lattice theory, multivariate polynomials,
graph theory, etc), which are computationally intractable even in the era of quantum computing.
Information Security
With cryptography it is possible to construct many security protocols that become the basic infrastructure for secure
communications such as SSL/TLS. These security protocols provide us with various security applications, for example,
copyright protection, electronic voting, cryptocurrency, and so on. This research group is engaged in the development
of new efficient cryptographic algorithms and implementation secure against physical attacks.

Lab. 1: Takagi

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Personal Information

Tsuyoshi Takagi
高木　剛

Department of Mathematical Informatics, 
Graduate School of Information Science and Technology
Professor

Room 343,Engineering Building 6, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 
Tel: 03-5841-6940 (ext. 26940)
Fax:

E-mail：takagi@mist.i.u-tokyo.ac.jp

[Home Page]

 

Biography

March 1995 M.Sc., Graduate School of Mathematics, Nagoya University, Japan
April 1995 Researcher, NTT Laboratories, Tokyo
October 1997 Guest researcher, Department of Computer Science, Technische Universitaet Darmstadt, Germany
October 1998 Researcher, NTT Laboratories, Germany
January 2001 PhD with honors, Department of Computer Science, Technische Universitaet Darmstadt, Germany
July 2002 Assistant Professor, Department of Computer Science, Technische Universitaet Darmstadt, Germany
April 2005 Associate Professor, School of Systems Information Science, Future University Hakodate, Japan
April 2008 Professor, School of Systems Information Science, Future University Hakodate, Japan
April 2010 Professor, Faculty of Mathematics, Kyushu University, Japan
April 2011 Professor, Institute of Mathematics for Industry, Kyushu University, Japan
April 2017 Professor, Graduate School of Information Science and Technology, The University of Tokyo, Japan

Research Themes

We investigate the theory and practice of cryptography which underpins the security of our information society.

● Cryptography
We study post-quantum cryptography based on the mathematical problems (such as coding theory, lattice theory, multivariate polynomials, graph theory, etc), which are computationally intractable even in the era of quantum computing.

● Information Security
We are engaged in the development of new efficient cryptographic algorithms and implementation secure against physical attacks, which can be used in our life, for example, copyright protection, electronic voting, cryptocurrency, and so on.

Main paper and books

Tsuyoshi Takagi (Ed), “Post-Quantum Cryptography – 7th International Workshop, PQCrypto 2016,” LNCS 9606, Springer 2016.
Kaoru Kurosawa, Tsuyoshi Takagi, “One-Wayness Equivalent to General Factoring,” IEEE Transactions on Information Theory, Vol.55, No.9, pp.4249-4262, 2009.
Tsuyoshi Takagi, “A Fast RSA-Type Public-Key Primitive Modulo pkq,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E87-A, No.1, pp.94-100, 2004.

 

Mathematical Informatics 7th Laboratory

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Computational Informatics Lab (Mathematical Informatics 7th Lab)
– Solve “troubles” in society – 		Webpage of Lab→
Satoru Iwata
Satoru Iwata
Professor		 Shinichi Tanigawa
Shinichi Tanigawa
Associate Professor
Ayumi Igarashi
Ayumi Igarashi
Associate Professor
Optimal Modeling
Modeling is the first step for solving real-world problems and understanding complex phenomena via a mathematical approach. However, there could be enormous different models to the same phenomenon. Furthermore, even in essentially equivalent models, the difficulty of the numerical computation varies due to variable choices and freedom in mathematical expressions in these models. Exploiting techniques from discrete mathematics, optimization, and statistics, we aim to establish a systematic methodology for selecting an optimal model from enormous possible models.

Discrete Computational Geometry
Computational geometry studies algorithms for solving geometric problems. Our particular interest is to understand the discrete structures behind geometric graphs and networks in engineering topics such as robotics, structural mechanics, and bioinformatics, and establish mathematical foundations for efficient algorithms.

Lab. 2: Sadakane

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Personal Information

Kunihiko Sadakane
Kunihiko Sadakane

Department of Mathematical Informatics, Graduate School of Information Science and Technology

Professor

Room 341, Engineering Building 6, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656
Tel: 03-5841-6955 (ext. 26955)
Fax: 03-5841-6955

E-mail：sada＠mist.i.u-tokyo.ac.jp

[Home Page]

Biography

March 1995 Bachelor Degree from Department of Information Science, Faculty of Science, The University of Tokyo
March 2000 Ph.D. from Department of Information Science, Graduate School of Science, The University of Tokyo
April 2000 Assistant Professor, Graduate School of Information Sciences, Tohoku University
April 2003 Associate Professor, Faculty of Information Science and Electrical Engineering, Kyushu University
April 2009 Associate Professor, National Institute of Informatics
March 2014 Professor, National Institute of Informatics
April 2014 Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo

Research Themes

・Algorithms and data structures for big data processing
・Theory and Applications of succinct data structures

Main paper and books

Wing-Kai Hon, Kunihiko Sadakane, Wing-Kin Sung: Breaking a Time-and-Space Barrier in Constructing Full-Text Indices. SIAM J. Comput. 38(6): 2162-2178 (2009)
Kunihiko Sadakane: Compressed Suffix Trees with Full Functionality. Theory Comput. Syst. 41(4): 589-607 (2007)
Kunihiko Sadakane, Gonzalo Navarro: Fully-Functional Succinct Trees. SODA 2010: 134-149

Taku Senoo

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Taku Senoo

妹尾 拓

Lecturer / Assistant Professor
Department of Information Physics and Computing,
Graduate School of Information Science and Technology, University of Tokyo

7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
Phone: +81.3.5841.6936
Fax: +81.3.5841.8604
Email: Taku_Seno@ipc.i.u-tokyo.ac.jp

[Homepage]

CV

Taku Senoo received the B.E. degree in applied physics from Waseda University in 2003, and the M.E. and the Ph.D. degrees in information physics and computing from the University of Tokyo in 2005 and 2008, respectively. He was a research fellow of japan society for the promotion of science from 2005 to 2008, a project research fellow from 2008 to 2010, a project assistant professor from 2010 to 2015, and an assistant professor from 2015 to 2018 at the University of Tokyo. He is currently a Lecturer / Assistant Professor of information physics and computing, the University of Tokyo.

Research theme

Dynamic Manipulation, Hand-arm Coordination, High-speed Visual Feedback Control, and Bipedal Robots.