Hi, my name is Andrew! I’m a second-year PhD student in Biomedical Data Science at Stanford University, where I am advised by James Zou and supported by the NSF Graduate Research Fellowship. I am broadly interested in problems at the intersection of AI and Science/Medicine, and I’m currently working on improving autonomous scientific discovery.

Before Stanford, I was a research associate with Marinka Zitnik at Harvard Medical School, where I worked on evolutionary reasoning of protein language models and molecular AI generalizability. I was also a research fellow in the Summer Institute in Biomedical Informatics (SIBMI) program at HMS.

I received my MS in Artificial Intelligence from Northwestern University in 2024, where I was advised by Joshua Glaser, and my BS in Bioinformatics from UC San Diego in 2023, where I was advised by Melissa Gymrek. Along the way, I’ve also been fortunate to be advised by Heather Moss and Kavita Sarin.

Get in touch

I’m always happy to chat about research or potential collaborations, so feel free to email me!

I’m also looking for motivated students with a strong computational background to work on AI for Science/Medicine. If you’re interested, please send me your resume.

Selected Papers

1. Unlocking LLM Creativity in Science through Analogical Reasoning
   Andrew Shen, Shaul Druckmann, James Zou. Advances in Neural Information Processing Systems (NeurIPS), 2026.
2. Evolutionary Reasoning Does Not Arise in Standard Usage of Protein Language Models
   Yasha Ektefaie*, Andrew Shen*, Lavik Jain, Maha Farhat, Marinka Zitnik. Advances in Neural Information Processing Systems (NeurIPS), 2025.
3. Evaluating generalizability of artificial intelligence models for molecular datasets
   Yasha Ektefaie, Andrew Shen, Daria Bykova, Maximillian G. Marin, Marinka Zitnik, Maha Farhat. Nature Machine Intelligence, 2024.