Ellen D. Zhong

Zhong_small.png

Email: zhonge [at] princeton.edu

Office: 314 Computer Science

I am an Assistant Professor of Computer Science at Princeton University where I lead the E.Z. Lab for Molecular Machine Learning. We are interested in problems at the intersection of AI and structural biology. In particular, our group focuses on developing methods for image analysis and 3D reconstruction that enable new discoveries in protein structure, dynamics, and interactions. For more information about our research, please visit our lab website.

Previously, I obtained my Ph.D. at MIT in 2022, where I developed deep learning methods for 3D reconstruction of dynamic protein structures from cryo-EM images. I have interned at DeepMind on the AlphaFold team, and prior to my Ph.D., I worked at D. E. Shaw Research on molecular dynamics algorithms for drug discovery.

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selected publications

See here for a full list of publications.
  1. cryodrgn_et_SI2.gif
    CryoDRGN-ET: deep reconstructing generative networks for visualizing dynamic biomolecules inside cells
    Ramya Rangan*, Ryan Feathers*, Sagar Khavnekar, Adam Lerer, Jake Johnston, Ron Kelley, Martin Obr, Abhay Kotecha, and Ellen D. Zhong
    Nature Methods, Jun 2024
  2. af3.jpg
    Accurate structure prediction of biomolecular interactions with AlphaFold 3
    Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, Alexander Pritzel, Olaf Ronneberger, Lindsay Willmore, Andrew J. Ballard, Joshua Bambrick, Sebastian W. Bodenstein, David A. Evans, Chia-Chun Hung, Michael O’Neill, David Reiman, Kathryn Tunyasuvunakool, Zachary Wu, Akvilė Žemgulytė, Eirini Arvaniti, Charles Beattie, Ottavia Bertolli, Alex Bridgland, Alexey Cherepanov, Miles Congreve, Alexander I. Cowen-Rivers, Andrew Cowie, Michael Figurnov, Fabian B. Fuchs, Hannah Gladman, Rishub Jain, Yousuf A. Khan, Caroline M. R. Low, Kuba Perlin, Anna Potapenko, Pascal Savy, Sukhdeep Singh, Adrian Stecula, Ashok Thillaisundaram, Catherine Tong, Sergei Yakneen, Ellen D. Zhong, Michal Zielinski, Augustin Žídek, Victor Bapst, Pushmeet Kohli, Max Jaderberg, Demis Hassabis, and John M. Jumper
    Nature, May 2024
  3. cryofire.gif
    Amortized Inference for Heterogeneous Reconstruction in Cryo-EM
    Axel Levy, Gordon Wetzstein, Julien Martel, Frederic Poitevin, and Ellen D Zhong
    In Neural Information Processing Systems (NeurIPS), Dec 2022
  4. covid_spike_short_small.gif
    Latent Space Diffusion Models of Cryo-EM Structures
    Karsten Kreis*, Tim Dockhorn*, Zihao Li, and Ellen D Zhong
    In NeurIPS Workshop on Machine Learning for Structural Biology (MLSB), Dec 2022
    Oral presentation
  5. cryodrgn2.png
    CryoDRGN2: Ab Initio Neural Reconstruction of 3D Protein Structures From Real Cryo-EM Images
    Ellen D Zhong, Adam Lerer, Joseph H Davis, and Bonnie Berger
    In International Conference on Computer Vision (ICCV), May 2021
  6. spliceosome.gif
    CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks
    Ellen D Zhong, Tristan Bepler, Bonnie Berger+, and Joseph H Davis+
    Nature Methods, Feb 2021
  7. cscs.png
    Learning the language of viral evolution and escape
    Brian Hie, Ellen D Zhong, Bonnie Berger+, and Bryan Bryson+
    Science, Feb 2021
  8. cryodrgn_iclr.png
    Reconstructing continuous distributions of 3D protein structure from cryo-EM images.
    Ellen D Zhong, Tristan Bepler, Joseph H Davis, and Bonnie Berger
    In International Conference on Learning Representations (ICLR), May 2020
    Spotlight presentation