Rohan Koodli

PhD Student at Stanford University

I'm a PhD student at the Stanford AI Lab (SAIL), advised by Ron Dror, where I develop ML methods for molecular biology applications. Previously, I graduated from the University of California, Berkeley, where I earned my Bachelor's and Master's degrees in EECS.

At Berkeley, I was a member of the Yosef Lab, where I developed VAE models for single-cell genomics data as part of the scvi-tools team. Previously, I built RNA design algorithms and benchmarks in Rhiju Das's Lab. I've also interned at Microsoft Research (advised by Eric Horvitz and Bruce Wittmann), Google, and Atomic AI.

In my free time, I enjoy running, playing soccer, and speed cubing. I support the Golden State Warriors and SF Giants, and have recently gotten into Formula 1. I also have a blog.

Recent Publications

A Graph Completion Method that Jointly Predicts Geometry and Topology Enables Effective Molecule Assembly
Rohan V Koodli, Alexander S Powers, Ayush Pandit, Chiho Im, Ron O Dror
arXiv, May 2025
Paper

MedSAGE: Bridging Generative AI and Medicinal Chemistry for Structure-Based Design of Small Molecule Drugs
Alexander S Powers, Tianyu Lu, Rohan V Koodli, Minkai Xu, Siyi Gu, Masha Karelina, Ron O Dror
bioRxiv, May 2025
Paper

Redesigning the Eterna100 for the Vienna 2 folding engine
Rohan V Koodli*, Boris Rudolfs*, Jonathan Romano*, Hannah K Wayment-Steele, William A Dunlap IV, Eterna Participants, Rhiju Das
bioRxiv, March 2025
Paper Code

Geometric deep learning for structure-based ligand design
Alexander S Powers, Helen H Yu, Patricia Suriana, Rohan V Koodli, Tianyu Lu, Joseph M Paggi, and Ron O Dror
ACS Central Science, November 2023
Paper

MultiVI: deep generative model for the integration of multimodal data
Tal Ashuach*, Mariano I Gabitto*, Rohan V Koodli, Giuseppe-Antonio Saldi, Michael I Jordan, Nir Yosef
Nature Methods, June 2023
Paper

PolyVI: Deep Generative Models for Gene Expression, Chromatin Accessibility, and Surface Protein Expression Data
Rohan V Koodli
Master's Thesis, May 2022
Thesis

EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame
Rohan V Koodli, Benjamin Keep, Katherine R Coppess, Fernando Portela, Eterna participants, Rhiju Das
PLOS Computational Biology, June 2019
Paper Code Cover art

Recent Blog Posts

A Guide to the Berkeley EECS 5th Year Master's Program