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 discovering new medicines. My recent work has focused on computationally guiding the engineering of cells using genetic perturbations.

I'm currently a PhD student at Stanford University advised by Jure Leskovec and Stephen Quake. I'm affiliated with the Department of Biomedical Data Science, the Stanford AI Lab and the Stanford Machine Learning Group.

I previously worked as a machine learning engineer at GSK where I led a cross-disciplinary team to biologically profile their 2M+ compound collection using complex multi-modal datasets and high throughput screening. I enjoyed the four years that I spent in industry designing robust machine learning systems that fit a healthcare context - from discovery all the way to diagnostics.

Curriculum Vitae:

[CV]

Publications:

Google Scholar page

Preprints

bioRxiv [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..
(* = equal contribution)

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

bioRxiv [2022] [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)

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..

arXiv [2021] On the opportunities and risks of foundation models
Bommasani, R., Hudson, D. A., ... Roohani, Y., ... Liang, P.

Conference Papers

NeurIPS [2021] Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development.
Huang K., Fu T., Gao W., Zhao Y., Roohani Y., Leskovec J., Coley C., Xiao C., Sun J., and Zitnik M..

NeurIPS Machine Learning for Health [2018] Predicting Language Recovery after Stroke with Convolutional Networks on Stitched MRI.
Roohani Y., Sajid N., Madhyastha P., Hope T., Price C.,

Journal Publications

Atmospheric Environment [2017] Impact of natural gas development in the Marcellus and Utica Shales on regional ozone and fine particulate matter levels.
Roohani, Y., Roy, A., Heo, J., Robinson, A., Adams, P.