Ellen D. Zhong
CV - Publications

Starting in July 2022, I will be an Assistant Professor of Computer Science at Princeton University.

Contact Info

Email: zhonge@princeton.edu
Twitter: @zhongingalong
Github: zhonge
Google Scholar

Latest News

July 2022: I have started my new appointment at Princeton University. New website coming soon!

July 2021: Our workshop on Machine Learning for Structural Biology is accepted at NeurIPS 2022!

June 2022: Invited talk at the Neural Fields in Computer Vision tutorial at CVPR.

Apr 2022: Invited talks at the CCP-EM Cryo-EM and Dynamics workshop, the VIB-VUB Structural Biology Center in Belgium, and the Deep Generative Models for Highly Structured Data workshop at ICLR.

Mar 2022: Invited talks at the 4th International Symposium on Cryo-3D Image Analysis, Brookhaven National Lab, John Hopkins University, Stanford University, the Society for Industrial and Applied Mathematics (SIAM) Conference on Imaging Science, the Vienna IMP/IMBA young investigators symposium, and the annual OpenEye CUP Scientific Meeting.

Feb 2022: Invited seminars at Princeton University and Columbia University.

Jan 2022: I defended my Ph.D. from MIT on "Machine learning for reconstructing dynamic protein structures from cryo-EM images"!

Jan 2022: Our CSCS NLP framework for viral escape prediction is being used to detect variants for rapid vaccine development by BioNTech.

Dec 2021: I was the general chair of the 2nd Machine Learning in Structural Biology Workshop at NeurIPS.

Nov 2021: Visited the UK to give invited seminars at the Francis Crick Institute and the MRC Laboratory of Molecular Biology (LMB) on "Machine learning for solving protein structures and dynamics".

Oct 2021: Attended the 3DEM Gordon Research Conference, where I was a discussion leader and gave introductory remarks on "Cryo-EM and AlphaFold in translational research".

Oct 2021: We presented our work, "CryoDRGN2: Ab initio neural reconstruction of 3D protein structures from real cryo-EM images" at ICCV.

Sept 2021: Completed my internship with the AlphaFold team at DeepMind!


I am interested in problems at the intersection of AI and biology. My research develops core machine learning techniques for computational and structural biology problems, with a particular focus on protein structure determination with cryo-electron microscopy (cryo-EM).


I recently received my Ph.D. from MIT, where I was advised by Bonnie Berger and Joey Davis. In my PhD, I created cryoDRGN, a neural method for 3D reconstruction of dynamic protein structures from cryo-EM images.


In the summer of 2021, I interned with John Jumper and the AlphaFold Team at DeepMind. Prior to MIT, I was a scientific programmer at D. E. Shaw Research where I developed algorithms and infrastructure for predicting protein-small molecule binding free energies from molecular dynamics simulations for drug discovery.


Selected Publications

Machine Learning for Reconstructing Dynamic Protein Structures from Cryo-EM Images
Ellen D. Zhong
Ph.D. dissertation. May, 2022.


CryoDRGN2: Ab Initio Neural Reconstruction of 3D Protein Structures From Real Cryo-EM Images
Ellen D. Zhong, Adam Lerer, Joey Davis, and Bonnie Berger.
International Conference on Computer Vision (ICCV), 2021.


CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks
Ellen D. Zhong, Tristan Bepler, Bonnie Berger, and Joey Davis.
Nature Methods, February 2021.


Learning the language of viral evolution and escape
Brian Hie, Ellen D. Zhong, Bonnie Berger, and Bryan Bryson.
Science, January 2021.


Exploring generative atomic models in cryo-EM reconstruction.
Ellen D. Zhong, Adam Lerer, Joey Davis, and Bonnie Berger
Machine Learning in Structural Biology Workshop at NeurIPS, December 2020.


Learning mutational semantics
Brian Hie, Ellen D. Zhong, Bryan Bryson, and Bonnie Berger.
Neural Information Processing Systems (NeurIPS), December 2020.


Structures of radial spokes and associated complexes important for ciliary motility
Miao Gui, Meisheng Ma, Erica Sze-Tu, Xiangli Wang, Fujiet Koh, Ellen D. Zhong, Bonnie Berger, Joseph H. Davis, Susan K. Dutcher, Rui Zhang, and Alan Brown.
Nature Structural and Molecular Biology, December 2020.


RNA timestamps identify the age of single molecules in RNA sequencing
Sam Rodriques, Linlin Chen, Sonya Liu, Ellen D. Zhong, Joe Scherrer, Ed Boyden, and Fei Chen.
Nature Biotechnology, October 2020.


Reconstructing continuous distributions of 3D protein structure from cryo-EM images.
Ellen D. Zhong, Tristan Bepler, Joey Davis, and Bonnie Berger.
International Conference on Learning Representations (ICLR), May 2020.
Spotlight Presentation at ICLR.
Oral Presentation and Best Paper award at MLCB satellite conference at NeurIPS 2019.


This site forked from here. Thank you!