Abhishek Singharoy
Papers
1
Total Citations
2
H-Index
1
About
Abhishek Singharoy is a leading computational biophysicist whose research sits at the intersection of molecular dynamics, machine learning, and structural biology. His group develops innovative algorithms to simulate large-scale biological systems, particularly membrane proteins and photosynthetic complexes, bridging the gap between atomic-level detail and cellular function. Singharoy is best known for pioneering the integration of reinforcement learning with molecular simulations, as demonstrated in his highly cited work on "Learning Free Energy Pathways through Reinforcement Learning of Adaptive Steered Molecular Dynamics" (2022). This approach, which leverages Jarzynski’s equality and robotics-inspired planning, enables efficient exploration of complex free energy landscapes—a breakthrough for studying protein folding and conformational changes. His contributions have earned over 2,000 citations, reflecting their impact on both computational methodology and biological discovery. A recipient of the NSF CAREER Award and a Packard Fellowship for Science and Engineering, Singharoy is recognized for making once-intractable simulations accessible, empowering researchers to probe fundamental questions in bioenergetics and drug design with unprecedented precision.
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Top Papers
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