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Ohzeki Lab
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A lab that draws on knowledge of physics to explore quantum computing and machine learning from a theoretical perspective.
AboutAbout the lab
Always something new, and a little different.
The Ohzeki Lab draws on mathematical science and physics to study problems in information science theoretically.
The lab aims to develop statistical mechanics of information, advance quantum machine learning, and apply quantum computing.
It also works on founding startups, collaborating with them, and pursuing industry-academia collaboration with large companies.
The lab is part of the Graduate School of Information Sciences at Tohoku University. At Institute of Science Tokyo, students can join it from the fourth year of undergraduate study or from graduate school by applying to the Department of Physics in the School of Science.
Key terms
- Quantum Annealing
- A computational method that uses a physical mechanism based on quantum properties to efficiently find a good combination among a huge number of possibilities
- Statistical Mechanics of Information
- A research field that applies methods from statistical mechanics in physics to algorithms and theory in information science
- Sparse Modeling
- A method of deriving answers from limited data on the assumption that only a few factors are truly important
ResearchResearch themes
The lab takes a theoretical approach to problems in information science, drawing on mathematical science and physics. In quantum annealing and sparse modeling, it also advances industrialization and applications together with companies.
*Illustrative imageQuantum Annealing
The lab studies technology that uses physical mechanisms to efficiently search for good combinations. It is advancing industrialization together with Sigma-i Co., Ltd. and Jij Inc.
*Illustrative imageStatistical Mechanics of Information
Using methods derived from physics, the lab gives algorithms and theory in information science solid guarantees and new perspectives. This provides theoretical support when handling large-scale, high-dimensional data.
*Illustrative imageMachine Learning and Quantum Machine Learning
The lab considers the mathematics of machine learning from the viewpoint of setting physical laws inside a computer and training the system with data as the conditions. New machine learning that uses quantum computers is also a subject of study.
*Illustrative imageSparse Modeling
This research is based on the idea that if only a few factors are truly important, limited data can be used to the fullest. The lab is advancing applications together with Hacarus Inc.
MembersFaculty
The Ohzeki Lab consists of faculty, visiting researchers, academic researchers, administrative assistants, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorMasayuki OhzekiPublications ↗
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: “Free-Energy-Landscape-Closeup” Tyler Savitski / CC BY-SA 4.0 (cropped)
- Quantum Annealing: “Quantum Annealing” Steve Jurvetson / CC BY 2.0 (cropped)
- Statistical Mechanics of Information: “Ising-tartan” Linas at English Wikipedia / CC BY-SA 3.0 (cropped)
- Machine Learning and Quantum Machine Learning: “Quantum Computer with Dispersive Background” OJB Quantum / CC BY 4.0 (cropped)
- Sparse Modeling: “Finite element sparse matrix” Oleg Alexandrov / Public domain (cropped)
- Related lab (向山研究室): “Cold atoms experiment 03” Tomasz Kawalec / CC BY-SA 4.0 (cropped)
- Related lab (賀川研究室): “Meissner effect p1390048” Mai-Linh Doan / CC BY-SA 3.0 (cropped)
- Related lab (慈道研究室): “Quantum Fluctuations” Derek Leinweber / CC BY-SA 4.0 (cropped)
- Related lab (素粒子論研究室
（伊藤・ 今村研究室） ): “CalabiYau5” Andrew J. Hanson / CC BY-SA 3.0 (cropped)
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