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Tsuda Lab
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A lab that takes on the development of new molecules and materials through machine learning and statistical science.
AboutAbout the lab
Reliable knowledge from data.
Tsuda Lab studies the theory of machine learning, data mining, and statistical science.
The lab applies this theory to a wide range of fields, including molecular biology, protein science, organic chemistry, and materials science.
In collaboration with experimental researchers at institutions such as the National Institute for Materials Science (NIMS) and RIKEN, the lab works on developing new molecules and materials.
Key terms
- Data mining
- Techniques for examining large amounts of data to dig out useful rules and patterns
- Ising machine
- A specialized computer built for computations that search for the best option among a huge number of combinations
- Quantum annealer
- A computer that uses quantum properties to search for the optimal solution to a combinatorial problem. It is a type of Ising machine
NewsLab news
A paper from joint research with Tohoku University and others received the Paper Award of the Society for Biotechnology, Japan
A researcher received the Outstanding Presentation Award from the Japanese Society of Breeding
ResearchResearch themes
The lab studies the theory of machine learning, data mining, and statistical science, as well as its applications in a wide range of fields. Its work includes designing new molecules and materials, discovering knowledge from life science data, and machine learning using quantum computing.
*Illustrative imageDeveloping new molecules and materials with machine learning
In collaboration with experimental researchers at NIMS, RIKEN, and elsewhere, the lab studies machine learning algorithms that automatically design organic compounds, proteins, peptides, and inorganic materials.
*Illustrative imageDiscovering reliable knowledge from diverse data
The lab develops methods for finding reliable knowledge in the diverse kinds of data encountered in the life sciences. Examples include CellTree and LAMP.
*Illustrative imageMachine learning using quantum computing
The lab studies machine learning algorithms that use Ising machines such as D-Wave's quantum annealers. Examples include FMQA and CONBQA.
MembersFaculty
The members of Tsuda Lab consist of faculty, researchers, doctoral, master's, and undergraduate students, and secretaries.As of 2026
- ProfessorKoji TsudaPublications ↗
- Assistant ProfessorRamesh Rajaby
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: “Caffeine molecule ball from xtal (1)” Jynto (more from this user) / CC0 (cropped)
- Developing new molecules and materials with machine learning: “Docking representation” Scigenis / CC BY-SA 4.0 (cropped)
- Discovering reliable knowledge from diverse data: “DNA microarray chip” ErikAbner / CC BY 4.0 (cropped)
- Machine learning using quantum computing: “D-Wave-Washington-1000Q” Mwjohnson0 / CC BY-SA 4.0 (cropped)
- Related lab (Takigawa Lab): “Docking representation 2” Scigenis / CC BY-SA 4.0 (cropped)
- Related lab (Kasahara Lab): “MinION portable sequencer” Mongan A.E. / CC BY 4.0 (cropped)
- Related lab (Kiryu Lab): “RNA structure (2)” Thomas Shafee / CC BY 4.0 (cropped)
- Related lab (Frith Lab): “DNA double helix 45” Jerome Walker,Dennis Myts / Public domain (cropped)
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