Yusuf Roohani - Group Lead, Machine Learning at Arc Institute

Yusuf Roohani

Group Lead, Machine Learning at Arc Institute

Palo Alto, California, United States

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Summary

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Senior

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Top School

Yusuf Roohani is a machine learning leader who combines 11 years of experience in ML and systems biology to build AI-driven tools for engineering cells and accelerating biological discovery. As Group Lead at the Arc Institute and a visiting scholar at Stanford CS, he leads efforts to create a "virtual cell" by integrating large AI models with high-throughput experimental data. His PhD work at Stanford under Jure Leskovec and Stephen Quake focused on computationally guiding genetic perturbations and experiment design, and he has industrialized ML systems for phenotypic drug discovery at GSK. An active contributor to open scientific tooling, he added drug-combo and CRISPR DNA-repair datasets and benchmarks to the widely used Therapeutics Commons (TDC) library, bridging data engineering and model development. Based in Palo Alto, he pairs deep academic rigor with practical production experience, uniquely positioning him to translate foundational models into experimental impact.

11 years of coding experience

6 years of employment as a software developer

Bachelor of Technology - BTech Mechanical Engineering, Bachelor of Technology - BTech Mechanical Engineering at Vellore Institute of Technology

Master of Science - MS, Master of Science - MS at Carnegie Mellon University

Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Stanford University

Github Skills (15)

machine-learning10

deeplearning-ai10

drug-discovery10

deep-learning10

python10

data-science9

ml9

bioinformatics9

pandas9

mle9

pytorch9

benchmark8

benchmarking8

data-engineering8

data-analysis8

Programming languages (3)

CSSJupyter NotebookPython

Github contributions (5)

mims-harvard/TDC

Dec 2020 - Feb 2021

Therapeutics Commons (TDC): Multimodal Foundation for Therapeutic Science

Role in this project:

Data Scientist / ML Engineer

Contributions:13 commits, 5 PRs, 5 comments in 1 month

Contributions summary:Yusuf primarily contributed to the implementation and integration of datasets related to drug combination and CRISPR DNA repair outcomes. They added data loading functionalities, target definitions, and benchmark configurations for the TDC library. This included modifying metadata and dataloader files, as well as the benchmark and utils files, to accommodate the new datasets and their specific metrics. Additionally, the user developed an MLP model for the drug combo benchmark.

therapeuticsdata-commonsbioinformaticsprecision-medicinescience

yhr91/GEARS_misc

Aug 2021 - Mar 2023

Contributions:93 commits, 1 PR, 47 pushes in 1 year 7 months

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