Koji Tsuda
Koji Tsuda researches molecular informatics. His shared team work combines automatic design methods with experiments by collaborating scientists. Tsuda coauthored a 2021 study of machine-learning-guided library design for enzyme evolution. The paper examines how training-data composition affects exploration of sequence space. In June 2022, Tsuda coauthored work on a fluorescent molecule designed with quantum-chemical computation and machine learning. His team programme develops AI methods for functional biomolecules and inorganic compounds. It studies Bayesian optimization and Monte Carlo tree search and synthesizes designed materials with experimental scientists.
- Now at
- University of Tokyo and National Institute for Materials Science
- Works
- 402
- Citations
- 14,319
- h-index
- 55
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2021
Learning-guided enzyme libraries
Tsuda coauthored a 2021 study of machine-learning-guided library design for enzyme evolution. The paper examines how training-data composition affects exploration of sequence space.
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2022
Fluorescent-molecule design
In June 2022, Tsuda coauthored work on a fluorescent molecule designed with quantum-chemical computation and machine learning.
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As of October 2026
Automatic molecular and material design
His team programme develops AI methods for functional biomolecules and inorganic compounds. It studies Bayesian optimization and Monte Carlo tree search and synthesizes designed materials with experimental scientists.
Sources and credits
Photo: www.riken.jp; Koji Tsuda profile photograph; creator not stated. License: Not stated by source. Source: riken.jp. Cropped to a square and resized. Ask us to remove or replace this photo.