Yusuf Roohani

Yusuf Roohani


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 generating large-scale cell perturbation data for training foundation models. Previously, I completed my PhD at Stanford University under the guidance of Jure Leskovec and Stephen Quake.

Curriculum Vitae:


Featured Publications:

For complete list: Google Scholar

Journal Publications

Nature Methods [2023] Towards Universal Cell Embeddings: Integrating Single-cell RNA-seq Datasets across Species with SATURN
Rosen Y.*, Brbic M.*, Roohani, Y.*, Swanson K., Li Z., Leskovec, J..

Nature Biotechnology [2023] [Code] GEARS: Predicting transcriptional outcomes of novel multi-gene perturbations
Roohani, Y., Huang, K., Leskovec J.
    Oral presentations and Awards:
     [Best Poster] Intelligent Systems For Molecular Biology (ISMB 2022)
     [Innovation Award] Society for Lab Automation and Screening (SLAS 2023)
     [Best Poster] [Video] Single-Cell Genomics Meets Data Science 2022
     [Video] Machine Learning for Computational Biology 2022 (MLCB2022)
     CRISPR Perturbations and Beyond 2022 (Wellcome Sanger Institute)
     [GitHub 150+ Stars]

(* = equal contribution)


arXiv [2023] [Code] Universal Cell Embeddings: A Foundation Model for Cell Biology
Rosen Y.*, Roohani Y.*, Agrawal A., Samotorcan L., Quake S., Leskovec J..
     [Media coverage] New York Times
     [Stanford BioX Interdiscplinary Initiatives Poster Award]

arXiv [2022] CausalBench: A Large-Scale Benchmark for Network Inference from Single-Cell Perturbation Data
Chevalley, M., Roohani, Y., Mehrjou, A., Leskovec, J., Schwab, P..

Conference Papers

ICLR [2024]: LLMs for Agents Workshop, MLGenX Workshop
BioDiscoveryAgent: An AI agent for designing genetic perturbation experiments
Roohani Y.*, Vora J.*, Huang Q.*, Steinhart Z., Marson A., Liang P., Leskovec J..
     [Best Poster] ICLR 2024 MLGenX Workshop

NeurIPS [2023] Zero-shot causal learning
Nilforoshan H.*, Moor M.*, Roohani Y., Chen Y., Surina A., Yasunaga M., Oblak S., Leskovec J..
     [Spotlight Presentation]