Papers
10
Total Citations
479
H-Index
6
About
Sergei V. Kalinin stands at the dynamic intersection of materials science, microscopy, and artificial intelligence, pioneering the integration of machine learning into experimental discovery and autonomous scientific workflows. His research has fundamentally advanced how scientists explore and characterize complex materials systems, with a particular emphasis on electron and scanning probe microscopy and metal halide perovskites. Kalinin's most influential contributions center on developing automated and autonomous experimental frameworks that harness AI to accelerate materials exploration. His work on chemical robotics and machine learning for lead halide perovskite stability (138 citations) demonstrated how intelligent automation could tackle longstanding commercialization bottlenecks in optoelectronics. Complementing this, his highly cited studies on automated microscopy (134 citations) established foundational principles for deploying ML-driven systems in real experimental environments, a vision he eloquently captured in "Probe Microscopy is All You Need." A recurring theme across his portfolio is the development of Bayesian optimization and active learning strategies, including human-in-the-loop frameworks that preserve researcher intuition while dramatically expanding experimental throughput. His work on deep learning for atomic-scale fabrication further illustrates his commitment to pushing microscopy toward genuine autonomy. With hundreds of citations accumulated across recent years alone, Kalinin's research is shaping the future of AI-driven materials science.
Research Focus
Key Achievements
Top Papers
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- 2Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy134 citations · 2021
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- 6Probe microscopy is all you need <sup>*</sup>18 citations · 2023
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