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Ellen Zhong

Photo of Ellen Zhong
Title/Position
Assistant Professor
Degree
Ph.D., Massachusetts Institute of Technology, 2022
zhonge  (@cs.princeton.edu) (609) 258-9075 314 Computer Science

Research

Interests: Machine learning, computational and structural biology, 3D computer vision, biological imaging

Research Areas:

Short Bio

Ellen Zhong is an Assistant Professor of Computer Science at Princeton University. She is interested in machine learning for structural biology and 3D computer vision with a particular focus on protein structure determination with cryo-electron microscopy (cryo-EM). Her work in cryo-EM reconstruction has addressed longstanding problems in visualizing dynamic protein structures and introduced fundamental innovations in implicit neural representations for computer vision. She has interned at DeepMind with the AlphaFold team and previously worked on molecular dynamics algorithms and infrastructure at D. E. Shaw Research. She obtained her Ph.D. from MIT where she worked with Bonnie Berger and Joey Davis and her B.S. from the University of Virginia where she worked with Michael Shirts.

Selected Publications

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.

Learning mutational semantics.
Hie B, Zhong ED, Bryson B, Berger B.
Neural Information Processing Systems (NeurIPS), 2020.

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. Spotlight presentation.

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