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Mathematical Planning and Informatics Lab
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The lab solves society's pain points with mathematical optimization models and algorithms.
AboutAbout the lab
Solving society's pain points
The Mathematical Planning and Informatics Lab studies a field called operations research (OR).
OR is a scientific technique for solving real-world problems and supporting decision-making by building mathematical models and using computers to find solutions.
In particular, the lab focuses on building models of problems as mathematical optimization problems and on developing algorithms to solve them.
The lab works on solving such pain points in fields including structural design, energy systems, and machine learning.
Key terms
- Operations Research
- A field that turns real-world problems into mathematical models and uses computation to find the best plan or decision
- Mathematical Optimization
- A method for mathematically finding the best answer within given conditions, such as minimizing cost
- Nonconvex
- In an optimization problem, a shape with many valleys. It makes finding the best answer difficult
NewsLab news
A doctoral student received the 44th Student Paper Award from the Operations Research Society of Japan
A doctoral student received the Best Presentation Award at "Optimization Modeling and Algorithms: Gathering of Young Researchers Shaping the Future 2026"
A master's student received the Research Encouragement Prize of the FY2025 Academic Encouragement Awards from the Society of Instrument and Control Engineers
Associate Professor Sato received the 2026 Control Division Pioneer Award from the Society of Instrument and Control Engineers
ResearchResearch themes
The lab models real-world problems as mathematical optimization problems and develops algorithms to solve them. It also pursues research that combines optimization theory with systems and control theory.
*Illustrative imageEfficient Methods for Continuous Optimization and Their Applications
Real-world problems often become large-scale, nonlinear, nonconvex continuous optimization problems. Where robustness to variability in the data is required, models known as robust optimization can also be useful. The lab aims to solve such problems efficiently and contribute to solving real-world problems.
*Illustrative imageSystems and Control Theory
The lab conducts research aimed at creating synergy between optimization theory and systems and control theory. It also aims to develop new optimization theory prompted by concrete problems in systems and control.
MembersFaculty
The lab's members consist of faculty, doctoral and master's students, and researchers from the RIKEN Center for Advanced Intelligence Project (AIP).As of 2026
- ProfessorAkiko TakedaPublications ↗
- Associate ProfessorKazuhiro SatoPublications ↗
- Assistant ProfessorShodai Takahashi
- Project Assistant ProfessorNaoki Marumo
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: “Vierwies wind farm, seen from a hot air balloon, Zele, 2026” DimiTalen / CC0 (cropped)
- Efficient Methods for Continuous Optimization and Their Applications: “Gradient ascent (contour)” user:Joris Gillis / Public domain (cropped)
- Systems and Control Theory: “Balancer with wine 3” ClarkH / CC BY-SA 3.0 (cropped)
- Related lab (Computational Informatics Lab): “SocialNetworkAnalysis” Martin Grandjean / CC BY-SA 4.0 (cropped)
- Related lab (Sadakane-Ito Lab (Mathematical Informatics Lab 2)): “TSP Deutschland 3” The original uploader was Kapitän Nemo at German Wikipedia. / Public domain (cropped)
- Related lab (Numerical Informatics Lab): “Soliton hydro” Christophe.Finot et Kamal HAMMANI / CC BY-SA 2.5 (cropped)
- Related lab (Cryptography and Mathematical Informatics Lab): “Enigma-IMG 0487-black” Rama / CC BY-SA 2.0 fr (cropped)
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