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I am an associate professor at the Department of Chemistry, Carnegie Mellon University. My current research interests focus on solving fundamental chemical problems with machine learning, molecular modeling, and quantum mechanics.

In our latest work, we present the 2nd generation of our atoms-in-molecules neural network potential (AIMNet2), which is applicable to species composed of up to 14 chemical elements in both neutral and charged states, making it a valuable model for modeling the majority of non-metallic compounds.

Generative AI as an Emerging Paradigm in the Chemical Sciences

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Featured Publications
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Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential.

Nature Chem. 2024, ASAP.
DOI:  10.1038/s41557-023-01427-3

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Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling

J. Chem. Inf. Model. 2023, 63, 2, 583–594  DOI: 10.1021/acs.jcim.2c01052

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Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis.

J. Am. Chem. Soc. 2021, 143, 42, 17677–17689. DOI:  10.1021/jacs.1c08181