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13 labs · 5 student voices
Other departments in Faculty of Science ›Faculties at The University of Tokyo ›
Masashi Sugiyama, Professor
AI & Machine Learning2 student voices
The Sugiyama-Yokoya-Ishida Lab studies the construction of the fundamental theory of machine learning, the development of practical algorithms, and their application to real-world problems. With advances in information and communication technology, computers have become able to carry out intellectual activities once thought possible only for humans, such as reasoning and creation. The Sugiyama Lab works on learning theory and algorithms, the Yokoya Lab on visual information processing and remote sensing, and the Ishida Lab on the evaluation and oversight of AI. The Sugiyama Lab also collaborates with companies and research institutes in Japan and abroad, taking on the challenge of solving real-world problems with cutting-edge machine learning algorithms.
Issei Sato, Professor
AI & Machine Learning1 student voices
Sato Lab studies "intelligence" in machine learning from the perspectives of memory, thinking, reasoning, and bias. The lab aims to combine empirical research with the development of theory for solving real-world problems. It values clearly defining the problems that society needs to solve and solving them through effective abstraction. It places more emphasis on discovering new problems worth solving than on solution methods that rely on advanced mathematics.
Naoki Kobayashi, Professor
Software & Computing1 student voices
Kobayashi Lab studies the foundational theory of software and methods for applying it to program verification. Systems for transportation, healthcare, e-commerce, and more run on software, and defects can lead to serious accidents. The lab therefore uses mathematical methods to verify and transform programs mechanically, aiming to improve their reliability and performance. What makes this field fascinating is that theories such as type theory, automata, and theorem proving connect directly to practical applications.
Tetsuo Shibuya, Professor
Medicine & Healthcare1 student voices
Shibuya Lab researches and develops medical data informatics technologies to accelerate medical science research in the era of personalized genomic medicine. With advances such as next-generation sequencers, a wide variety of large-scale data is accumulating in medical science at a furious pace. The lab advances research on big data algorithms and related topics from two sides: applications to bioinformatics and the foundations of information science. The lab is located in the Human Genome Center at the Institute of Medical Science, and also uses the center's supercomputer for its research.
Ma Lei, Associate Professor
AI & Machine Learning0 student voices
The Ma Lab studies quality assurance for building trustworthy AI systems, in the area where software engineering and AI overlap. The lab works on testing, analysis, verification, interpretation, and attack and defense for software that incorporates machine learning.
Shinya Takamaeda, Professor
Software & Computing0 student voices
The Takamaeda Lab (CASYS) studies computer architecture, the field that deals with the structure and design techniques of computers. Its work includes application-specific hardware, in-memory computing, methods for co-designing machine learning and hardware, and compilers that support hardware design. The lab also researches software that makes computers easier to use, such as compilers and programming systems. Because of building renovation, the faculty offices and the lab have temporarily relocated (as of September 2026).
Yoshihide Yoshimoto, Associate Professor
Quantum & Condensed Matter0 student voices
The Yoshimoto Lab studies fields at the boundary between computational science and computer science, centered on first-principles electronic structure calculation. Computational science has grown alongside the development of computers as a new scientific method, following experiment and theory. Today, as the way computers work has become more complex, computational science and computer science need to work together. The lab aims to provide education and research that help foster exchange between these two fields.
Takahiro Shinagawa, Professor
Software & Computing0 student voices
The Shinagawa Lab studies system software, centered on operating systems (OS) and virtualization software. System software holds special privileges that allow it to control the entire computer, and it greatly affects the performance and security of the whole system. Through new system abstractions, the lab aims to improve the security and performance of today's computers. Because Building 7 of the Faculty of Science is under renovation, the lab has temporarily moved to Building 8 of the Faculty of Engineering (faculty offices) and Building 12 of the Faculty of Engineering (student rooms), as of September 2026.
Ken-ichi Kawarabayashi, Professor
Software & Computing0 student voices
The Kawarabayashi Lab conducts research centered on algorithms and discrete mathematics. Rather than aiming for applications from the start, the lab focuses on fundamental and theoretical research. In algorithms research, the lab works on everything from improving computational complexity and theoretically analyzing correctness to developing techniques that make implementations fast. In discrete mathematics research, the lab explores mathematically deep theory while also developing techniques that can be used in other fields, such as algorithms.
Yusuke Miyao, Professor
AI & Machine Learning0 student voices
The Miyao Lab studies how to enable computers to understand the language that people use every day (natural language). To do so, it is necessary to clarify the mechanisms by which natural language and human thought operate. The lab studies fundamental natural language analysis techniques and mathematical models, including syntactic parsing, semantic analysis, and grounding. The lab's strength lies in research that draws on linguistics, such as syntax and formal semantics, and on computer science, such as formal grammar and machine learning.
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