ELLEN D. ZHONG
Machine learning for the molecular sciences
01 About
I am an Assistant Professor of Computer Science at Princeton University, where I am also affiliated with the Princeton Laboratory for Artificial Intelligence, the Center for Statistics and Machine Learning, the Omenn–Darling Bioengineering Institute, and the Department of Molecular Biology. I work on problems at the intersection of AI and the molecular sciences, with the goal of building methods that enable new scientific discoveries.
My research program spans methodological research in AI and computational imaging, as well as close collaboration with experimentalists in molecular biology and chemistry. A focus of my group is developing deep learning methods for 3D reconstruction of protein structure from imaging data, and we develop open-source software in active use by the structural biology community.
Our work has been recognized with the NIH Director's New Innovator Award, the Schmidt Sciences AI2050 Early Career Fellowship, a Major Society Award from the Microscopy Society of America, the Eric and Wendy Schmidt Transformative Technology Fund Award, and the E. Lawrence Keyes, Jr./Emerson Electric Co. Faculty Advancement Award. I am grateful for support from the NIH, the Chan Zuckerberg Initiative, Schmidt Sciences, Janssen Pharmaceuticals, Generate Biomedicines, and Princeton University.
I received my Ph.D. from MIT in 2022 before joining the Princeton faculty. Previously I worked at Google DeepMind on the AlphaFold team, and at D. E. Shaw Research on molecular dynamics algorithms for drug discovery.
I also spend some time with companies and research institutes. My current industry and professional engagements include:
- Generate Biomedicines (Professor in Residence)
- The Chan Zuckerberg Imaging Institute (Scientific Advisory Board)
- Deep Apple Therapeutics (Scientific Advisory Board)
02 Contact
- zhonge [at] princeton.edu
- Office
- 314 Computer Science
- Department of Computer Science
Princeton University, 35 Olden St
Princeton, NJ 08540
03 News
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Awarded the K.H. Kuo Award for Outstanding Young Scientist in Structural Biology.
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Delivered a Simons Foundation Presidential Lecture, “Algorithms for Biomolecular Structure Determination at the Proteome Scale.” CryoHype is accepted to CVPR 2026.
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Featured in the Y Combinator conversation “The Future of AI Molecular Discovery.”
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The lab presents at NeurIPS 2025 in San Diego — talks at the Machine Learning for Structural Biology (MLSB) and Frontiers of Probabilistic Inference (FPI) workshops.
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Named an AI2050 Early Career Fellow by Schmidt Sciences. The 2025 Community-Wide Assessment of Cryo-EM Heterogeneous Reconstruction Algorithms (CAHRA) launches.
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Awarded the NIH Director's New Innovator Award.
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CryoDRGN-AI is published in Nature Methods.
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Interviewed for a Quanta Magazine feature on machine learning for structural biology.
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Started as an Assistant Professor at Princeton Computer Science.