Kirthevasan Kandasamy
Papers
5
Total Citations
275
H-Index
5
About
Kirthevasan Kandasamy is a leading researcher at the intersection of machine learning, Bayesian optimization, and autonomous scientific discovery. His most impactful work centers on dramatically accelerating materials design by combining Gaussian process bandit optimization with robotic experimentation. In his landmark 2020 paper, "Autonomous Discovery of Battery Electrolytes with Robotic Experimentation and Machine Learning" (164 citations), Kandasamy demonstrated a fully autonomous platform that uses machine learning to guide a robotic test-stand through hundreds of sequential experiments, discovering novel battery electrolytes far faster than traditional trial-and-error methods. This work exemplifies his broader contributions to multi-fidelity optimization, where he pioneered techniques for efficiently optimizing expensive black-box functions by leveraging cheap approximations—a framework detailed in his highly cited 2016 paper (68 citations). By enabling scientists to explore vast chemical and material spaces with minimal human intervention, Kandasamy’s research is reshaping how we approach complex design problems. His achievements highlight a powerful vision: marrying algorithmic innovation with automation to accelerate discovery in energy, materials science, and beyond.
Research Focus
Key Achievements
Top Papers
- 1
- 2Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations68 citations · 2016
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- 5Multi-fidelity Gaussian Process Bandit Optimisation7 citations · 2019