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Mathematical Planning Lab [Graduate School of Information Science and Technology]
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This lab explores decision-making for planning and control for execution through mathematics.
AboutAbout the lab
Exploring decision-making and control through mathematics
The Mathematical Planning Lab (Fujisaki Lab) studies mathematical theory and its applications for decision-making, which is about making plans, and control, which is about carrying them out.
The lab works on modeling, analysis, and design of dynamical systems; performance evaluation and guarantees for randomized algorithms; multi-agent systems; data-driven control; and security and privacy.
The lab aims to establish mathematical approaches to decision-making and control as methodologies in engineering and the social sciences.
Key terms
- Robust optimization
- An optimization problem that involves uncertainty. Solving it makes it possible to reach decisions that are not affected by uncertain conditions.
- Randomized algorithm
- A solution method that makes active use of random numbers to compute quickly while guaranteeing the accuracy of the resulting values.
- Dependable control
- Control for properly handling the spread of fluctuations and failures in multilayer networks, such as power grids and information networks.
NewsLab news
A master's student received the SCI Student Presentation Award at the 70th Research Presentation Conference of the Institute of Systems, Control and Information Engineers
A master's student received the FY2025 Graduate School of Information Science and Technology Award
A master's student received the SCI Student Presentation Award at the 69th Research Presentation Conference of the Institute of Systems, Control and Information Engineers
A master's student received the FY2024 SICE Outstanding Student Award
ResearchResearch themes
The lab studies mathematical theory and its applications for decision-making, which is about making plans, and control, which is about carrying them out. It works on robust optimization, which deals with problems involving uncertainty, among other topics.
Fast Methods for Solving Robust Optimization
Robust optimization, which deals with optimization problems that involve uncertainty, is difficult to solve in a realistic amount of time. The lab develops methods based on randomized algorithms, which make active use of random numbers, to solve these problems quickly while guaranteeing accuracy.
*Illustrative imageDependable Control of Large-Scale Systems
The lab was working on building the fundamental theory of dependable control, aiming to realize highly stable power systems that can accommodate the large-scale introduction of renewable energy. It aimed to create a methodology that integrates systems and control theory with dependable technologies.
MembersFaculty
The members of the Mathematical Planning Lab (Fujisaki Lab) are faculty members, administrative assistants, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorYasumasa Fujisaki
- Assistant ProfessorKaoru Teranishi
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: “Hellenic Autonomous Vehicle (Dashboard)” Electrical Eng25 / CC BY 4.0 (cropped)
- Dependable Control of Large-Scale Systems: “Renewable Energy on the Grid” Kenueone / CC0 (cropped)
- Related lab (Mathematical Systems Science Lab [Graduate School of Information Science and Technology]): “Frank-Wolfe Algorithm” Stephanie Stutz / CC BY 4.0 (cropped)
- Related lab (Information Photonics Lab): “Bose-Einstein condensate, a cloud of super-cooled Rubidium atoms in a Laser trap on an Optical table - In a game of catch & release, the atoms will shoot up a 30 ft. tall Atomic fountain - Stanford” Steve Jurvetson from Menlo Park, USA / CC BY 2.0 (cropped)
- Related lab (Nonlinear Mathematics Lab [Graduate School of Information Science and Technology]): “Lorenz Attractor from Gauss-Legendre” Mgolden96 / CC BY-SA 4.0 (cropped)
- Related lab (Nano Surface and Interface Engineering Lab): “Scanning tunneling microscope-MHS 2237-IMG 3817-white” Rama / CC BY-SA 3.0 fr (cropped)
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