Papers

11

Total Citations

260

H-Index

6

About

Shigeru Kobayashi is a versatile researcher whose career spans two distinct yet equally impactful domains: autonomous materials synthesis and rescue robotics. His most celebrated contribution lies at the intersection of artificial intelligence and materials science, where his 2020 paper on autonomous materials synthesis using machine learning and robotics garnered an impressive 183 citations, establishing him as a pioneering voice in the emerging field of self-driving laboratories. His subsequent work on Bayesian optimization for materials synthesis — exploring one-, two-, and three-dimensional parameter spaces — further refined computational strategies for navigating complex chemical landscapes, while his 2023 study on autonomous electrode material discovery for lithium batteries demonstrates the real-world promise of these methods. Earlier in his career, Kobayashi made meaningful contributions to disaster response technology, developing the UMRS series of rescue robots following the devastating 1995 Hanshin-Awaji earthquake. His work addressed critical challenges including door-opening mechanisms, human victim detection via CO₂ sensing, and coordinated multi-robot search systems. Together, these two research threads reveal a researcher consistently motivated by high-stakes, real-world problems — whether saving lives in disaster zones or accelerating humanity's search for next-generation functional materials.

Research Focus

Key Achievements

6
H-Index
11
Papers
260
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Autonomous materials synthesis by machine learning and robotics
183 citations · 2020
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 27
🏛 Institutions: Tokyo Institute of Technology, Kobe City College of Technology, Kobe University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago