# Koji Tsuda

> Japanese information scientist

**Wikidata**: [Q47146530](https://www.wikidata.org/wiki/Q47146530)  
**Source**: https://4ort.xyz/entity/koji-tsuda

## Summary
Koji Tsuda is a Japanese computer scientist and university teacher known for his work in machine learning and computational biology. He is a professor at the University of Tokyo and has made significant contributions to the application of machine learning in materials science and bioinformatics.

## Biography
- Born: 1972
- Nationality: Japanese
- Education: Kyoto University (educated_at)
- Known for: Machine learning applications in computational biology and materials science
- Employer(s): University of Tokyo (employer), Kyoto University (educated_at)
- Field(s): Machine learning, computational biology, informatics, materials science

## Contributions
Koji Tsuda has developed machine learning algorithms for drug discovery and materials design, particularly focusing on graph-based learning methods for molecular structures. His research group at the University of Tokyo has created software tools for predicting molecular properties and designing new materials. Tsuda has published extensively on kernel methods for structured data, including applications in chemoinformatics where his algorithms help identify potential drug candidates by analyzing molecular structures. His work on material informatics uses machine learning to accelerate the discovery of new functional materials, reducing the time and cost of experimental trials. Tsuda has also contributed to bioinformatics through methods for analyzing biological networks and predicting protein functions.

## FAQs
### Q: What is Koji Tsuda's main area of research?
A: Koji Tsuda specializes in machine learning applications for computational biology and materials science, particularly developing algorithms for analyzing molecular structures and designing new materials.

### Q: Where does Koji Tsuda work?
A: Koji Tsuda is a professor at the University of Tokyo, where he leads research in machine learning and its applications to scientific discovery.

### Q: What are some applications of Koji Tsuda's research?
A: His research has been applied to drug discovery, materials design, and bioinformatics, helping to predict molecular properties and accelerate the development of new functional materials.

## Why They Matter
Koji Tsuda's work has transformed how machine learning is applied to scientific discovery, particularly in chemistry and biology. His algorithms for analyzing molecular structures have become standard tools in chemoinformatics, enabling researchers to screen millions of compounds for potential drug candidates without physical testing. In materials science, his machine learning approaches have significantly reduced the time required to discover new materials with desired properties, accelerating innovation in areas like energy storage and electronics. Tsuda's contributions to kernel methods for structured data have influenced how researchers handle complex molecular and biological data, making previously intractable problems computationally feasible. His interdisciplinary approach bridging computer science with chemistry and biology has helped establish the field of materials informatics as a distinct discipline.

## Notable For
- Developing graph-based machine learning algorithms for molecular structure analysis
- Pioneering applications of machine learning in materials informatics
- Creating software tools for drug discovery and materials design
- Mentoring Elisabeth Georgii, who completed her doctorate under his supervision
- Establishing computational approaches that reduce experimental costs in materials science

## Body
### Academic Background
Koji Tsuda received his education at Kyoto University, one of Japan's most prestigious institutions. His academic training laid the foundation for his interdisciplinary approach combining computer science with chemistry and biology.

### Research Focus
Tsuda's research centers on machine learning methods for structured data, particularly graphs and sequences that represent molecules and biological networks. He has developed kernel methods that can handle the complexity of molecular structures, enabling computers to "understand" chemical compounds in ways that facilitate automated analysis and design.

### Software Development
His research group has created several open-source software packages for machine learning applications in chemistry and biology. These tools implement his algorithms for molecular property prediction and materials design, making his methods accessible to researchers worldwide.

### Industry Impact
The algorithms developed by Tsuda's group are used in pharmaceutical companies for virtual screening of drug candidates, significantly reducing the need for laboratory experiments. His materials informatics approaches have been adopted by materials science laboratories to guide experimental synthesis of new compounds.

### Academic Leadership
As a professor at the University of Tokyo, Tsuda has supervised numerous graduate students and postdoctoral researchers who have gone on to establish their own research programs in computational science. His former student Elisabeth Georgii completed her doctorate under his supervision, demonstrating his role in training the next generation of computational scientists.

## Schema Markup
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  "@type": "Person",
  "name": "Koji Tsuda",
  "jobTitle": "Professor of Computer Science",
  "worksFor": {
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  "nationality": {
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  "birthDate": "1972",
  "alumniOf": {
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  "description": "Japanese computer scientist known for machine learning applications in computational biology and materials science"
}

## References

1. BnF authorities
2. Czech National Authority Database
3. Mathematics Genealogy Project
4. Virtual International Authority File
5. [Source](https://id.ndl.go.jp/auth/ndlna/00914791)
6. KAKEN
7. CiNii Research