Jacky Chen
Ph.D. Student
CMU-Pitt Joint Ph.D. Program in Computational Biology
I am a third-year Ph.D. student in the Joint Carnegie Mellon–University of Pittsburgh Ph.D. Program in Computational Biology, advised by David Koes. My research focuses on machine learning methods for molecular discovery and sampling. Prior to my Ph.D., I worked with Alan Cheng at Merck on deep learning for ADMET prediction. I received my undergraduate degree from Johns Hopkins University, where I worked with Jeffrey Gray on diffusion models for protein docking.
Education
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Carnegie Mellon University
University of Pittsburgh
Joint Ph.D. Program in Computational Biology -
Johns Hopkins University
Experience
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Merck & Co., Inc.
Modeling & Informatics -
Johns Hopkins University
Gray Lab
Selected Publications
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WELP: Weighted Ensemble in the LooP for Committor LearningNeurIPS, 2026
BibTeX
@inproceedings{chen2026welp, title={{WELP}: Weighted Ensemble in the {LooP} for Committor Learning}, author={Chen, Jacky and Aggarwal, Rishal and Koes, David Ryan}, booktitle={Advances in Neural Information Processing Systems}, year={2026} } -
NeurIPS, 2025Paper arXiv Code
BibTeX
@inproceedings{aggarwal2025boltznce, title={{BoltzNCE}: Learning Likelihoods for {Boltzmann} Generation with Stochastic Interpolants and Noise Contrastive Estimation}, author={Aggarwal, Rishal and Chen, Jacky and Boffi, Nicholas and Koes, David}, booktitle={Advances in Neural Information Processing Systems}, volume={38}, pages={167195--167227}, year={2025}, doi={10.52202/085713-5574} } -
Journal of Chemical Information and Modeling, 2025Paper ChemRxiv
BibTeX
@article{chen2025data, title={Data Scaling and Generalization Insights for Medicinal Chemistry Deep Learning Models}, author={Chen, Jacky and Chung, Yunsie and Tynan, Jonathan and Cheng, Chen and Yang, Song and Cheng, Alan C.}, journal={Journal of Chemical Information and Modeling}, volume={65}, number={12}, pages={5887--5898}, year={2025}, publisher={American Chemical Society}, doi={10.1021/acs.jcim.5c00538} }