Gina El Nesr

Hey there! I am 5th year biophysics Ph.D. Candidate in the Protein Design Lab at Stanford University. I also serve as chair and program organizer for the Machine Learning in Structural Biology Workshop at NeurIPS. My research interests are in developing deep learning algorithms for the design of de novo proteins towards enzymatic function. More broadly, I am interested in modeling the dynamic nature of proteins for new-to-nature functions.

When I'm not doing research, you can probably find me weightlifting, hiking, eating, or with friends.

If you are interested in getting in touch or collaborating, please feel free to reach out!

Learning millisecond protein dynamics from what is missing in NMR spectra
Hannah K. Wayment-Steele* Gina El Nesr*, Ramith Hettiarachchi, Hasindu Kariyawasam, Sergey Ovchinnikov, Dorothee Kern (* = equal contribution)
bioRxiv '25 | Biophysics
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Editorial: Machine Learning for Structural Biology
Gabriele Corso† Gina El Nesr†, Hannah K. Wayment-Steele† († = authors listed in alphabetical order)
PRX Life '24 | Special Collection MLSB
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An all-atom protein generative model
Alexander E. Chu, Jinho Kim, Lucy Cheng, Gina El Nesr, Richard W. Shuai, Minkai Xu, Po-Ssu Huang.
PNAS '24 | Proceedings of the National Academy of Sciences
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Singular value decomposition of protein sequences as a method to visualize sequence and residue space
Autum R. Baxter-Koenigs*, Gina El Nesr*, Doug Barrick. (* = equal contribution)
PS '22 | Protein Science
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Machine Learning for Protein Engineering
Talked about learning milisecond protein dynamics from what is missing in NMR spectra.
Virtual Talk
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Machine Learning for Protein Engineering
Talked about SVD for visualizing sequence and residue space.
Virtual Talk
video| abstract

NSF Graduate Research Fellowship
2022 | Stanford University

Institute for Data Intensive Engineering and Science (IDIES) Student Summer Research Fellowship
2020 | Johns Hopkins University

Jason H.P. and Beverly Kravitt Fund Fellow
2019 | Johns Hopkins University

Woodrow Wilson Research Fellowship
2018 | Johns Hopkins University

Guest Editor
2024-Present | American Physical Society - PRX Life

Workshop Organizer + Reviewer
2023-Present | Machine Learning in Structural Biology (MLSB) @ NeurIPS

Workshop Reviewer
2024 | GEM.bio @ International Conference on Learning Representations (ICLR)

Workshop Proposal Committee
2024 | International Conference on Machine Learning (ICML)