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27 labs · 2 student voices
Other departments in School of Computing ›Faculties at Institute of Science Tokyo ›
Katsuki Fujisawa, Professor
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Fujisawa Lab aims to solve social problems by integrating the real world and virtual space. Using AI, mathematical optimization, graph analysis, and high-performance computing, the lab builds real-world applications through industry-academia collaboration. The lab runs simulations and optimization on digital twins, which recreate real machines and facilities in virtual space. It also works on techniques for analyzing huge networks, smart factories, and optimizing the movement of people and goods.
Yu Yokoi, Associate Professor
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Yokoi Lab studies discrete mathematics and algorithms. It deals with problems on graphs and sets, and matching problems in which participants have ranked preferences. The lab aims to design algorithms that achieve optimality and fairness for such problems. Its members are interested in combinatorial optimization, matroid theory, stable matching, game theory, and mathematical economics.
Zin Arai, Professor
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Arai Lab studies the mathematics of dynamical systems and computational topology. The lab aims to use computer science to build a bridge between pure mathematics and concrete problems. It is particularly interested in real and complex Hénon maps and the structure of their parameter spaces. The lab is also pursuing research that applies topological and computational methods to fields such as chemistry, engineering, and biology.
Kenji Yasunaga, Associate Professor
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The Yasunaga Lab studies a range of techniques in theoretical computer science, including cryptography and error-correcting codes. The lab explores the boundary between what can and cannot be achieved when computation is expressed mathematically. It also covers foundational questions such as how to measure the security of cryptographic schemes, and approaches to security based on game theory. Research topics are decided through discussion between students and faculty members.
Satoshi Takabe, Associate Professor
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The Takabe Lab studies information engineering in a broad sense from the perspectives of machine learning, information theory, and statistical mechanics. Its subjects include signal processing, optimization, error-correcting codes, network science, and statistical machine learning. It is particularly interested in the average properties of randomly generated problems and systems. For such problems, the lab proposes and analyzes efficient, high-performance algorithms.
Sumita Hanna, Associate Professor
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The Sumita Lab studies the theory of combinatorial optimization. Combinatorial optimization is the task of choosing the best one among the combinations that satisfy given conditions. The lab not only designs algorithms that solve problems, but also theoretically analyzes their performance, such as solution quality and running time, and the limits of that performance. It aims to reveal the structure behind why problems are hard or easy to solve.
Nishibata Shinya, Professor
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The Nishibata Lab studies the mathematical analysis of nonlinear partial differential equations that arise in mathematical physics and related areas. Hyperbolic-elliptic systems, shock waves, and model equations for semiconductors are listed as the lab's research keywords. The work falls within mathematical analysis, a field spanning analysis and the theory of differential equations.
Shunsuke Tsuchioka, Associate Professor
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The Tsuchioka Lab studies representation theory and quantum algebras. If number theory is the study of numbers, representation theory is the study of symmetry. One of the lab's goals is to discover formulas like those of Ramanujan, using Lie theory, quantum algebras, and categorification.
Takafumi Kanamori, Professor
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The Kanamori Lab studies machine learning and mathematical statistics. Machine learning and statistical techniques that dig out and make use of the treasure hidden in data are having a major impact on society. The lab aims to understand information quantitatively from a mathematical perspective and to apply the results across data science in general. It also works on information geometry and on optimization methods for learning algorithms.
Ken Wakita, Associate Professor
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The Wakita Lab studies interactive data visualization techniques and visual analytics systems. Data visualization has three pillars: scientific visualization, information visualization, and visual analytics. This lab works on the latter two. For example, the lab is building a system that analyzes the reference relationships among math-related pages on the Japanese edition of Wikipedia, allowing users to grasp the overall structure of the articles.
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