Interests: Machine learning, computational and structural biology, 3D computer vision, biological imaging
Ellen Zhong is an Assistant Professor of Computer Science at Princeton University. She is interested in problems at the intersection of AI and biology. Her research develops machine learning methods for computational and structural biology problems with a focus on protein structure determination with cryo-electron microscopy (cryo-EM). She obtained her Ph.D. from MIT in 2022, advised by Bonnie Berger and Joey Davis, where she developed deep learning algorithms for 3D reconstruction of dynamic protein structures from cryo-EM images. She has interned at DeepMind with John Jumper and the AlphaFold team and previously worked on molecular dynamics algorithms and infrastructure for drug discovery at D. E. Shaw Research. She obtained her B.S. from the University of Virginia where she worked with Michael Shirts on computational methods for studying protein folding.
For more information about her research and group, please visit her group website: https://ezlab.princeton.edu/
Amortized inference for heterogeneous reconstruction in cryo-EM
Levy A, Wetzstein G, Martel J, Poitevin F, Zhong ED.
Neural Information Processing Systems (NeurIPS), 2022.
CryoDRGN2: Ab initio neural reconstruction of 3D protein structures from real cryo-EM images.
Zhong ED, Lerer A, Davis JH, Berger B.
International Conference on Computer Vision (ICCV), 2021.
CryoDRGN: Reconstruction of heterogeneous cryo-EM structures using neural networks.
Zhong ED, Bepler T, Berger B, Davis JH.
Nature Methods, 2021. doi:10.1038/s41592-020-01049-4.
Learning the language of viral evolution and escape.
Hie B, Zhong ED, Berger B, Bryson B.
Science, 2021. doi:10.1126/science.abd7331.
Reconstructing continuous distributions of 3D protein structure from cryo-EM images.
Zhong ED, Bepler T, Davis JH, Berger B.
International Conference on Learning Representations (ICLR), 2020.