Ayumi Igarashi

Personal Information

Ayumi Igarashi
Ayumi Igarashi

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

Room 330, Engineering Building 6, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 
Tel: 03-5841-6549, (ext. 26549)
Fax:

E-mail:igarashi@mist.i.u-tokyo.ac.jp

[Home Page]

 

Curriculum Vitae

March 2012 Bachelor of Policy and Planning Sciences, University of Tsukuba
March 2014 Master of Engineering, University of Tsukuba
March 2018 Ph.D in Computer Science, University of Oxford
April 2018 – March 2020 Postdoctoral Fellow of Japan Society for the Promotion of Science
April 2020 – September 2022 Assistant Professor, National Institute of Informatics
October 2022 – Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo

Research Themes

I work on computational social choice. My main research focus is on designing fair resource allocation mechanisms that satisfy desirable fairness and efficiency properties. Applications include rent division among roommates, property division among family members, course assignment to students, and so on. I am also interested in developing multi-winner voting rules, where each group of voters has a fair influence on the outcome.

Selected Publications


Nawal Benabbou, Mithun Chakraborty, Ayumi Igarashi, Yair Zick, Finding Fair and Efficient Allocations for Matroid Rank Functions, ACM Transactions on Economics and Computation, 9 (4), pp. 1–41, 2021.

Vittorio Bilo, Ioannis Caragiannis, Michele Flammini, Ayumi Igarashi, Gianpiero Monaco, Dominik Peters, Cosimo Vinci, William S. Zwicker, Almost Envy-free Allocations with Connected Bundles, Games and Economic Behavior, 131, pp. 197–221, 2022.

Haris Aziz, Ioannis Caragiannis, Ayumi Igarashi, and Toby Walsh, Fair Allocation of Combinations of Indivisible Goods and Chores, The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019, pp. 53–59.

Robert Bredereck, Edith Elkind, and Ayumi Igarashi, Hedonic Diversity Games, The 18th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2019, pp. 565–573.

 

Takeru Matsuda

Personal Information

Takeru Matsuda
Takeru Matsuda

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

Room 344, Engineering Building 6, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 
Tel: +81-3-5841-6910 (ext. 26910)
Fax:

E-mail:matsuda@mist.i.u-tokyo.ac.jp

[Home Page]

 

Curriculum Vitae

Mar. 2012 Bachelor degree from Department of Mathematical Engineering and Information Physics, Faculty of Engineering, The University of Tokyo
Mar. 2014 Master degree from Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Mar. 2017 Ph. D. from Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Apr. 2017 Assistant Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Jun. 2020 Unit Leader, RIKEN Center for Brain Science, RIKEN
Oct. 2022 Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo

Research Themes

1. Theoretical statistics: mathematical foundation of data analysis

2. Computational statistics: development of algorithms for data analysis

3. Applied statistics: modeling and analysis of data from various fields such as neuroscience

Main paper and books


Takeru Matsuda and William E. Strawderman. Estimation under matrix quadratic loss and matrix superharmonicity. Biometrika, 109, 503–519, 2022.

Takeru Matsuda, Masatoshi Uehara and Aapo Hyvarinen. Information criteria for non-normalized models. Journal of Machine Learning Research, 22(158):1–33, 2021.

Takeru Matsuda and Yuto Miyatake. Estimation of ordinary differential equation models with discretization error quantification. SIAM/ASA Journal on Uncertainty Quantification, 9, 302–331, 2021.

Takeru Matsuda. Statistical analysis of kimariji in competitive karuta (in Japanese). Japanese Journal of Applied Statistics, 49, 1–11, 2020.

Takeru Matsuda and Fumiyasu Komaki. Time series decomposition into oscillation components and phase estimation. Neural Computation, 29, 332–367, 2017.

 

Mathematical Data Science Lab. (Mathematics and Informatics Center)

Mathematical Data Science Lab. (Mathematics and Informatics Center) HomePage→
Yoshihiro Kanno
Yoshihiro Kanno

Professor
Tomonari Sei
Tomonari Sei

Professor
Teppei Ogihara
Teppei Ogihara

Associate Professor
Mathematics of design optimization
Design optimization is the methodology that utilizes mathematical
optimization to improve the rationality and sophistication of design
processes in engineering. We mainly focus on developing mathematical
modelings and numerical algorithms for solving diverse optimal design
problems.

Statistical Modeling of Dependence
We develop statistical models and inference methods of dependence
structure hidden in various data.
The keywords are copula theory, directional statistics, optimal
transport and algebraic statistics.

Statistical Analysis of Stochastic Processes
We study statistical methods for stochastic processes, especially parameter estimation methods such as maximum likelihood and Bayesian methods, and their asymptotic theories.
We are also conducting applied research on high-frequency data for the Japanese and U.S. stock markets.