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Intelligence Science Lab
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A division that scientifically investigates human intelligence and builds technologies that support intellectual activity.
AboutAbout the lab
Exploring human intelligence and behavior to support intellectual activity
The Intelligence Science Lab aims to scientifically investigate human intelligence and behavior, establish foundational information science technologies that support human intellectual activity, and develop applications of them.
Rather than a single lab, it is a division made up of multiple labs, each working on different themes such as cognitive science, machine learning, natural language processing, and multi-agent systems.
It is a division of the Department of Information Science and Technology in the Graduate School of Information Science and Electrical Engineering, and is also introduced as a lab of the Information Science course in the Department of Physics, Faculty of Science.
Key terms
- multi-agent system
- A system containing multiple intelligent entities (agents). Systems in which humans and software coexist are also covered.
- recommendation
- Technology for suggesting products and the like to users.
- large language model
- The underlying mechanism of chat systems such as ChatGPT.
ResearchResearch themes
The Intelligence Science Lab scientifically investigates human intelligence and behavior, and aims to establish foundational information science technologies that support human intellectual activity. The labs in the division cover a wide range of fields, including cognitive science, machine learning, natural language processing, multi-agent systems, sensory information processing, and human informatics.
*Illustrative imageHuman Cognition and Driver Assistance
With engineering applications in mind, the lab scientifically studies how the human mind works. Topics include the development of automated driving and driver assistance systems, communication between self-driving vehicles and pedestrians or drivers, and perception and cognition in virtual reality environments.
*Illustrative imageMachine Learning, Data Mining, and AI
In light of advances in large language models, the lab develops AI methods that understand sophisticated meaning, and works on their applications. It also covers recommendation (suggesting products to users) and learning and discovery from images, video, and robots.
*Illustrative imageMachine Learning Theory for Smart Decision-Making
For problems of predicting the future from past data and making decisions, the lab develops smart decision-making methods, mainly using machine learning. Conversely, it also studies how to apply those decision-making methods to optimization problems in machine learning.
*Illustrative imageDesigning Systems with Multiple Agents
The lab studies systems containing multiple intelligent entities (agents) as multi-agent systems. It describes problems such as assigning students to labs and e-commerce within the frameworks of game theory and microeconomics, and works on the design and analysis of systems and social institutions.
MembersFaculty
The members of the Intelligence Science Lab consist of professors, associate professors, and assistant professors.As of 2026
- ProfessorWilly Wong
- ProfessorYoshihiro Okada
- ProfessorKazunori Shidoji
- ProfessorEinoshin Suzuki
- ProfessorEiji Takimoto
- ProfessorYoichi Tomiura
- ProfessorKohei Hatano
- Associate ProfessorDaisuke Ikeda
- Associate ProfessorMiki Kaneko
- Associate ProfessorKei Kimura
- Associate ProfessorHiroto Saigo
- Associate ProfessorZhaohong Sun
- Associate ProfessorTaiki Todo
- Associate ProfessorEita Nakamura
- Assistant ProfessorYoshinori Katayama
- Assistant ProfessorMiyuki Kishimura
- Assistant ProfessorTetsu Matsukawa
- Assistant ProfessorHaruna Fujihira
- Assistant ProfessorXin Huang
- Assistant ProfessorXinhang Lu
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Brain-inspired cognitive architecture” Baba 496 / CC0 (cropped)
- Human Cognition and Driver Assistance: “2008 Maruti Suzuki Alto Dashboard 02” Vjdeep / CC BY 3.0 (cropped)
- Machine Learning, Data Mining, and AI: “Artificial Intelligence relation to Generative Models subset, Venn diagram” The Original Benny C / CC BY-SA 4.0 (cropped)
- Machine Learning Theory for Smart Decision-Making: “Inferential Statistics Decision Making Table” Jtneill / CC BY-SA 3.0 (cropped)
- Designing Systems with Multiple Agents: “MIREA Interdepartmental educational and scientific laboratory Intelligent Autonomous and multi-agent robotic systems 7” Нечаева Лилия Александровна / CC BY-SA 4.0 (cropped)
- Related lab (計算科学講座): “Von Karman vortices off Rishiri Island, Japan” NASA / Public domain (cropped)
- Related lab (数理情報講座): “ZUSE Z22 vacuum tube 2” Sammlung der Medien und Wissenschaft / CC BY 4.0 (cropped)
- Related lab (量子宇宙物理理論研究室): “Universum” Heikenwaelder Hugo, Austria, , www.heikenwaelder.at / CC BY-SA 2.5 (cropped)
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