Mathematical Informatics of Social Complex Systems

Laboratory for Mathematical Informatics of Social Complex Systems
-Language , Communication, and Financial Markets-
(Research Center for Advanced Science and Technology)
Webpage of Lab→
Kumiko Tanaka-Ishii
Kumiko Tanaka-Ishii

Professor

We explore the universal properties underlying large-scale social systems through mathematical models derived by computing with big data obtained from large-scale resources. Using these models, we explore new ways of engineering to aid human social activities.

1. Analysis of large-scale social systems by applying complex systems theory
Common scaling properties are known to hold across various large-scale social systems. Using real, large-scale data, we study the nature of these properties, from viewpoints such as complexity, degree of fluctuation, and self-similarity, and construct a mathematical model that explains them.
 
2. Deep/Machine learning methods for complex systems
We discuss the potential and limitations of deep learning and other machine learning techniques with respect to the nature of complex systems, and we study directions for improvement. Moreover, we explore unsupervised and semi-supervised methods for state-of-the-art learning techniques.
 
3. Mathematical informatics across language, financial markets, and communication
We explore common universal properties underlying language, finance, and communication, through computing with various kinds of large-scale data, and we apply our understanding of those properties to engineering across domains. For example, we study financial market analysis by using blogs and other information sources, and we simulate information spread on a large-scale communication network.

seisanken – omi

Profile

Takahiro Omi(近江 崇宏)
近江 崇宏

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

Aihara lab., Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan.
Tel: +81-3-5452-6697 (Ext. 56697)
Fax:

E-mail:omi@sat.t.u-tokyo.ac.jp

Curriculum Vitae

March 2007 Bachelor of Science from Faculty of Science, Kyoto University
March 2009 Master of Science from Department of Physics, Graduate School of Science, Kyoto University
March 2012 Ph.D. in Science from Department of Physics, Graduate School of Science, Kyoto University
April 2012 Researcher, Japan Science and Technology
April 2013 Japan Society for the Promotion of Science Fellowship for Young Scientists
April 2016 Project Research Associate, Institute of Industrial Science, The University of Tokyo
April 2018 Project Associate Professor, Institute of Industrial Science, The University of Tokyo

Research Themes

Our main topics is time-series analysis. We especially focus on the statistical analysis of point process data, which describe events that occur irregularly in time. Our research includes
(1) the development of estimation and forecast method based on Bayesian statistics and
(2) its application to earthquake, economic, and social data.

Selected Publications

T. Omi, Y. Hirata, and K. Aihara,
“Hawkes process model with a time-dependent background rate and its application to high-frequency financial data”,
Physical Review E 96, 012303 (2017).

T. Omi, Y. Ogata, Y. Hirata, and K. Aihara,
“Forecasting large aftershocks within one day after the main shock”,
Scientific Reports 3, 2218 (2013).

T. Omi and S. Shinomoto,
“Optimizing time histograms for non-Poissonian spike trains”,
Neural Computation 23, 3125 (2011).

Lab. 1: Nuida

Personal Information

Koji Nuida
Koji Niida

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

Room 354,Engineering Building 6, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 
Tel: 03-5841-6959 (ext. 26959)
Fax:

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

[Home Page]

 

Biography

March 2001 Bachelor (Science) Department of Mathematics, Faculty of Science, The University of Tokyo, Japan
March 2003 M.S. (Mathematical Sciences) Graduate School of Mathematical Sciences, The University of Tokyo, Japan
March 2006 Ph.D. (Mathematical Sciences) Graduate School of Mathematical Sciences, The University of Tokyo, Japan
April 2006 National Institute of Advanced Industrial Science and Technology, post-doc researcher, Japan
April 2007 National Institute of Advanced Industrial Science and Technology, researcher
March 2013 National Institute of Advanced Industrial Science and Technology, senior researcher, Japan
October 2014 Japan Science and Technology Agency, PRESTO (additional; until March 2018)
April 2018 Associate Professor, Graduate School of Information Science and Technology, The University of Tokyo, Japan

Research Themes

The main subjects of my research are cryptography and information security technologies that are bases of security for various information technologies. Examples are as follows:

● Theory of cryptography
Designs and security analyses for cryptographic schemes, particularly aiming at realizing long-term security against future adversaries with highly advanced computational powers.

● Privacy-preserving data mining
Secure computation schemes that enable to utilize data while preserving the security/privacy, in various application areas.

● Fundamental mathematics
Mathematical theory including group theory and discrete mathematics, and their application to cryptography.

Main paper and books

Koji Nuida, Goichiro Hanaoka, “On the security of pseudorandomized information-theoretically secure schemes”, IEEE Transactions on Information Theory, vol.59, no.1, pp.635-652, 2013.
Koji Nuida, Kaoru Kurosawa, “(Batch) Fully Homomorphic Encryption over Integers for Non-Binary Message Spaces”, in: EUROCRYPT 2015 (Part I), LNCS vol.9056, pp.537-555, 2015.
Kana Shimizu, Koji Nuida, Gunnar Ratsch, “Efficient Privacy-Preserving String Search and an Application in Genomics”, Bioinformatics, vol.32, no.11, pp.1652-1661, 2016.
Robert B. Howlett, Bernhard Muhlherr, Koji Nuida, “Intrinsic Reflections and Strongly Rigid Coxeter Groups”, Proceedings of the London Mathematical Society, vol.116, no.3, pp.534-574, 2018.