Accelerating cancer research with data-driven innovation and machine learning
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Research Focus

We advance the understanding of cancer and cancer therapy by integrating and deriving insight from complex data including functional genetic screens, chemical screens, and 'omics data. We develop tools and applications that empower researchers around the world to explore and analyze these data. We work collaboratively to ensure data science aspects are considered from experimental design to interpretation of results. As a team, we share ideas and best practices as well as create a supportive and open environment where we can learn and develop.

Precision cancer medicine

We build predictive models to predict cancer vulnerabilities from genomic profiles of tumors and cancer cell lines.

Cancer Targets Identification

We integrate functional screening and 'omics data to identify novel cancer targets as well as drugs for repurposing.


We develop computational methods and tools to facilitate the analysis of CRISPR screening in cancer models.

Small-molecule screens

We analyze highly-multiplexed small-molecule screening data from the PRISM platform to discover novel cancer therapeutic leads.

Our Team

Katie Campbell

Director, Cancer Data Science

Philip Montgomery

Associate Director

Josh Dempster

Group Leader, Computational Biology

Sowmya Iyer

Mustafa Kocak

Computational Scientist II

Isabella Boyle

Associate Computational Biologist II

Barbara De Kegel

Computational Scientist

Jessica Cheng

Software Engineer

Alexandra Mourey

Software Engineer

Randy Creasi

Senior Software Engineer

Simone Zhang

Bioinformatics Engineer

Nayeem Aquib

Software Engineer

Sarah Wessel

Software Engineer

Sam Maffa

Associate Computational Biologist I

YuhJong Liu

Associate Computational Biologist I

Alison Cameron

Associate Computational Biologist I

Alvin Qin

Leading Computational Biologist

Yejie Yun

Associate Computational Biologist II

Heejo Choi

Computational Biologist

Lauren Golden

Computational Scientist II

Yao He

Computational Scientist II

Dev Gulati

Associate Computational Biologist II

Devin McCabe

Principal Bioinformatics Engineer

Ashish George

Computational Scientist II


Aviad Tsherniak

Founder of CDS

James McFarland

Director of Data Science, Generate Biomedicines

Mike Burger

Senior Scientist, Merck

Jérémie Kalfon

Senior Computational Associate

David Wu

MD-PhD Student, University of Pennsylvania

William Colgan

Granduate Student, Computational Biology, MIT

Andrew Boghossian

Neuroscience, UCSF

Kwabena Ofori-Atta

MD-PhD Student, Tri-Institutional Program

Andrew Tang

Sr. Visual Designer

Han Xu

Associate Professor, MD Anderson

Robin Meyers

Graduate Student, Genetics, Stanford University

Jared Jacobsen

Studying for AI Research

Li Wang

Computational Biologist, 10X Genomics

Jordan Bryan

Graduate Student, Statistics, Duke University

Kailash Nakagawa

Undergraduate Student, Stanford University

Quinton Wessells

Graduate Student, Biomedical Informatics, Stanford University

Remi Marenco

Bioinformation Lead, Cancer Cell Line Factory

Guillaume Kugener

Medical Student, USC

Zandra Ho

Medical Student, Brown

Andy Jones

Graduate Student, Computer Science, Princeton University

Jordan Rossen

Graduate Student, Epidemiology, Harvard University

Vickie Wang

MD-PhD Student, Neuroscience, University of Pennsylvania

Mariya Kazachkova

Graduate Student, Biomedical Sciences, UCSD

Phoebe Moh

Graduate Student, Computer Science, University of Maryland

Allie Warren

Associate Computational Biologist II

Neekesh Dharia

Medical Director, Genentech

Nishant Jha

Software Engineer

Josephine Lee

Senior Software Engineer

Yejia Chen

Senior Software Engineer

Gwen Miller

PhD Student, Bioinformatics and Integrative Genomics, Harvard University

Javad Noorbakhsh

Principal Scientist, Kojin Therapeutics

Josh Pan

Research Scientist, Genomics, DeepMind

Ashir Borah

PhD Student, Biological and Medical Informatics; University of California San Francisco

Lena Joesch-Cohen

Associate Computational Biologist II

CDS Outings

Join Us

About the team:

We are an interdisciplinary group dedicated to accelerating cancer research. We help design and analyze large-scale experiments, develop new statistical tools and machine learning methods, write papers, produce datasets used by tens of thousands of researchers around the world, and guide research and development for applying new technologies to cancer research.

The success of cancer precision medicine requires determining optimal treatments given the detailed genomic and molecular information encoded in each patient’s tumor. CDS aims at accelerating precision cancer medicine by creating computational software (such as Chronos) and interactive exploratory tools (such as the DepMap portal) to help researchers understand the mechanisms of genetic and chemical vulnerabilities across all human cancers. To achieve this, CDS collaborates with multiple groups and research labs (e.g., DepMap, PRISM, CCLF, Sellers Lab, Getz lab etc) to assemble the most detailed and comprehensive characterization of the genomic and molecular features of preclinical cancer models.

In the Cancer Data Science team, we pride ourselves on the quality and rigor of our science, but just as much on our work culture. We believe in a team with strong connections, a healthy work-life balance, and a high degree of psychological safety. We look for candidates with diverse backgrounds, strengths, and perspectives, who are willing to challenge and be challenged. We are also a highly collaborative team, working closely with cancer biologists, experimentalists, project managers, and clinicians.

We don't currently have any open positions, but we're always interested to hear from computationalists and software engineers who are excited about driving precision cancer medicine with team science.


Selected publications

A first-generation pediatric cancer dependency map

Neekesh V. Dharia et al.
Nature Genetics
March 2021

Integrated cross-study datasets of genetic dependencies in cancer

Clare Pacini et al.
Nature Communications
March 2021

Global computational alignment of tumor and cell line transcriptional profiles

Allison Warren et al.
Nature Communications
January 2021

Defining a Cancer Dependency Map

Aviad Tsherniak et al.
July 2017

Accompanying website:

Other publications

Contact Us

Cancer Data Science

Broad Institute of MIT and Harvard
415 Main Street
Cambridge, MA 02142

Email: contactcds at