Hey there! I am currently a second-year biophysics Ph.D. Candidate in the Possu Huang Lab at Stanford University. My research interests are in developing deep learning algorithms for the design of de novo functional proteins. I currently also serve as a program organizer for the Machine Learning in Structural Biology Workshop at NeurIPS.

I graduated with a BS in Computer Science, BA in Biophysics, and BS in Applied Math and Statistics from Johns Hopkins University. At Hopkins, I was an undergraduate researcher with Doug Barrick and previously the-late James Taylor. I also worked in the Integrated Imaging Center as a cryo-EM research assistant under the supervision of Michael McCaffery. I spent a lot of my time in undergrad as a TA for Biophysical Chemistry and Protein Engineering & Biochemistry Lab.

I was previously a process development intern at Shire Pharmaceuticals (now Takeda Pharmaceuticals) and a software development intern at Senscio Systems.

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


An all-atom protein generative model
Alexander E. Chu, Lucy Cheng, Gina El Nesr, Minkai Xu, Po-Ssu Huang
bioRxiv '23 | bioRxiv
pdf| abstract| cite

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
abstract| cite

Recorded Talks

Machine Learning for Protein Engineering
Talked about SVD for visualizing sequence and residue space.
Virtual Talk
video| abstract

Selected Awards

NSF Graduate Research Fellowship
2022 | Stanford University

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

Woodrow Wilson Research Fellowship
2018 | Johns Hopkins University