Sara Mostafavi

Sara Mostafavi is a computer scientist whose machine-learning work links genomics with gene function and disease biology. She earned a BSc in Computer Science and Life Sciences from the University of Toronto in 2004, an MS in Computing Sciences from Queen's University in 2006, and a PhD in Computer Science at Toronto in 2011; her thesis integrated large genomics datasets to predict gene function. Before UBC, she completed a Stanford CS postdoc with Daphne Koller; at UBC she served as an Assistant Professor in Statistics and Medical Genetics and a faculty member at the Vector Institute, held a Canada Research Chair from 2015 to 2020, and received a Canada CIFAR Artificial Intelligence Chair in 2018. She joined UW's Allen School in fall 2020, led a 2023 CZI-funded project on methods for predicting how cells respond to environmental factors, coauthored ExplaiNN, a Genome Biology paper on interpretable and transparent neural networks for genomics, and coauthored AssayBench in 2026. During AY 2024–25 and AY 2025–26, she took leave from UW to lead Genentech's AI for Biology and Translation department; as of October 2026, she is Head of AI for Biology & Translation.

Now at: University of Washington and Roche
Works: 261
Citations: 33,118
h-index: 65
Badges: Bridge
Boomerang
Wayfarer

Publication numbers from OpenAlex, as of 27 October 2026.

Timeline

2004–2011

Computer science and biology degrees

She earns a B.Sc. in Computer Science and Life Sciences from the University of Toronto in 2004 and an M.S. in Computing Sciences from Queen's University in 2006. In 2011, she completes a Ph.D. in Computer Science at Toronto under Quaid Morris; her thesis develops machine-learning methods that integrate large-scale genomics datasets to predict gene function.
By 2020

Stanford postdoc and UBC chairs

Before UBC, she completes a postdoc in Stanford's Computer Science department with Daphne Koller. From 2015 to 2020, she holds a Canada Research Chair in Computational Biology. In 2018, she is an Assistant Professor in UBC's Departments of Statistics and Medical Genetics and a faculty member at the Vector Institute; UBC awards her a Canada CIFAR Artificial Intelligence Chair.
2020

Joining the Allen School

In fall 2020, she joins the Allen School faculty after five years as a faculty member at UBC. Her research focuses on machine-learning and statistical methods for studying human disease and on tools that help distinguish meaningful relationships from spurious ones across high-dimensional genomic datasets.
2023

A CZI project on cell responses

In 2023, she leads a CZI-funded project with Su-In Lee to develop methods for predicting how cells respond to different environmental factors. The project extends her use of deep neural networks to study how genetic variation affects disease susceptibility.
2023

ExplaiNN genomics paper

In 2023, she coauthors ExplaiNN, a Genome Biology paper on interpretable and transparent neural networks for genomics.
2024–2026

Leading AI for Biology at Genentech

She takes leave from UW during AY 2024–25 and AY 2025–26 to lead Genentech's AI for Biology and Translation (AIBT) department.
2026

AssayBench and CRISPR screen prediction

In 2026, she coauthors AssayBench, a benchmark for phenotypic screen prediction built from 1,920 publicly available CRISPR screens.
As of October 2026

Head of AI biology at Genentech

She is Head of AI for Biology & Translation at Genentech and an Associate Professor of Computer Science & Engineering and Adjunct Associate Professor of Genome Sciences at the University of Washington.

Career

Since 2024RocheHead of AI for Biology & Translation
Since 2020University of WashingtonAssociate Professor of Computer Science & Engineering
2019–2020Vector InstituteFaculty Member
2015–2020University of British ColumbiaAssistant Professor
2012–2015Stanford UniversityPostdoctoral Fellow