Gina Nesr is a PhD candidate in Biophysics at Stanford developing deep learning methods with experimental validation to design de novo enzymes and probe allosteric mechanisms. With nine years of cross-disciplinary experience spanning computer science, biophysics, and applied math, she combines computational modeling of protein dynamics with hands-on wet-lab and cryo-EM backgrounds. An NSF GRFP awardee and visiting researcher at UW–Madison, she also teaches and organizes community efforts like the MLSB Workshop at NeurIPS and guest edits special collections in PRX Life. Her work bridges method development and experimental validation, enabling new-to-nature enzymatic functions informed by dynamics rather than static structures.
8 years of coding experience
1 year of employment as a software developer
Johns Hopkins University
Dual Enrollment, Dual Enrollment at Worcester Polytechnic Institute
High School, 11-12, High School, 11-12 at Massachusetts Academy of Math and Science at WPI
Doctor of Philosophy - PhD, Biophysics, Doctor of Philosophy - PhD, Biophysics at Stanford University
This repository contains a set of scripts for performing singular value decomposition on protein multiple sequence alignments, and analyzing the results.
This repository contains a set of scripts for performing singular value decomposition on protein multiple sequence alignments, and analyzing the results.
Contributions:3 PRs, 37 pushes, 5 branches in 2 years 6 months
analyzingsequencedecompositionsingularalignments
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