Yusuf Roohani

About:

I design new machine learning approaches for modeling biological systems. In particular, I'm interested in how artificial intelligence can inform better experiment design for biological discovery. My recent work has focused on computationally guiding the engineering of cells using genetic perturbations.

Currently, I lead a machine learning group at the Arc Institute, where we are working on building a virtual cell by combining large AI models with strategically scaled data generation. Previously, I completed my PhD at Stanford University under the guidance of Jure Leskovec and Stephen Quake. Prior to that, I worked for four years in early stage drug discovery at GSK.

firstname.lastname@arcinstitute.org

Curriculum Vitae:

Arc Machine Learning Group Members

• Abhinav Adduri (Arc ML Research Scientist)
• Arshia Nayebnazar (UC Berkeley EECS undergrad student)
• Basak Eraslan (Arc ML, Bioinformatics Senior Scientist)
• Beatrice Bevilacqua (Arc ML Research Scientist)
• Chris Carpenter (Arc Senior Research Assistant)
• Leon Hafner (Arc ML Research Fellow)
• Rishi Verma (Arc ML Engineer)

Past Members

• Apratim Dey (Stanford Statistics Postdoc)
• Dhruv Gautam (UC Berkeley EECS MS student)
• Yangyi Shen (Stanford CS MS student, now Stanford CS PhD student)
• Mingze Dong (Yale Comp Bio PhD student)
• Francis Chalissery (Arc ML Research Fellow, now at OpenAI)
• Rohan Shah (UPenn Math undergraduate)
• Alishba Imran (UC Berkeley EECS undergraduate, now at EvolutionaryScale)
• Andrew Lee (Stanford CS MS student, now at Need AI)
• Sanjay Nagaraj (Stanford CS MS student)

Featured Publications:

Journal Publications

Preprints

Conference Papers