insitro Hires AI and Machine Learning Visionary, Emily Fox, Ph.D., as Senior Vice President of AI/ML
SOUTH SAN FRANCISCO, Calif.–(BUSINESS WIRE)–insitro, a machine learning-powered drug discovery and development company, today announced the appointment of Emily Fox, Ph.D., as senior vice president of AI/machine learning. In this role, she will oversee those areas as well as data science and computational biology, inclusive of data modalities that span genetics, omics, imaging, clinical data, and molecular design. Dr. Fox, a professor in the Department of Statistics and Department of Computer Science at Stanford University, has made groundbreaking contributions in the application of machine learning in healthcare, with her pioneering work directly translating into patient impact.
“AI leaders of Emily’s caliber who simultaneously have an understanding of biology and health are rare, and we are privileged to have recruited her to lead our AI/ML teams,” said Daphne Koller, Ph.D., co-founder and CEO. “Her groundbreaking work in machine learning, alongside her track record in translating research into impactful applications in healthcare, aligns perfectly with our mission to revolutionize drug discovery through data-driven approaches. Emily’s stellar track record of innovation and leadership, recognized with prestigious awards and accolades, underscores her exceptional contributions to the field. We’re thrilled to welcome her wealth of knowledge and visionary insight to our team at insitro.”
“The transformative power of machine learning in redefining biology is increasingly recognized, and insitro is uniquely positioned to translate this potential to improve human health through the seamless integration of massive biological and clinical datasets together with cutting-edge machine learning methods, providing insights never uncovered before,” said Dr. Fox. “These insights are going to be transformative in accelerating the discovery of novel targets and the development of molecules that interact with them, marking a new era in therapeutic innovation. As someone passionate about machine learning for human health, to be at a company where machine learning is a core part of the mission and is integrated into the entire pipeline from data collection to scientific discovery and drug development is truly inspiring.”
Prior to joining Stanford, Dr. Fox established, grew, and led the Health AI team at Apple, where she was a Distinguished Engineer. At Apple, her team collaborated cross-functionally on health and wellness projects leveraging Apple’s ecosystem of devices and software, as well as studies with partners including Aetna, Johnson & Johnson, Eli Lilly, and the Seattle Flu Study. She also served as the Amazon Professor of Machine Learning in the Paul G. Allen School of Computer Science & Engineering and Department of Statistics at the University of Washington. Her academic research has focused on discovering interpretable latent structure from complex, high-dimensional scientific and clinical datasets, with an emphasis on data arising in genomics and neuroscience, and on machine learning for healthcare applications, including the use of wearable devices and other in-the-wild sensing modalities.
Her work has been recognized with her selection as a CZ Biohub – San Francisco Investigator (2022-2027) and serving as the NeurIPS Program co-chair in 2019. She has also been awarded a Presidential Early Career Award for Scientists and Engineers (PECASE), Sloan Research Fellowship, ONR Young Investigator award, and NSF CAREER award. Her Ph.D. thesis was recognized with the Leonard J. Savage Thesis Award in Applied Methodology and MIT EECS Jin-Au Kong Outstanding Doctoral Thesis Prize.
Fei-Fei Li, an AI pioneer, Sequoia Professor of Computer Science and founding Co-Director of Stanford’s Human-Centered AI Institute, Stanford University, said, “Having had the privilege of knowing and working with both Emily Fox and Daphne Koller for many years, I’ve witnessed firsthand their definitive contributions to machine learning, particularly in healthcare. With Emily joining insitro, their combined efforts in leveraging AI for biology discovery and drug development are set to revolutionize the field. It’s collaborations like these that highlight the power of diverse minds in AI, driving not just technological progress, but societal betterment as well.”
About insitro
insitro is a drug discovery and development company applying machine learning (ML) and generative AI to data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. These data are used to develop ML models that expand insitro’s data tensor via imputation, uncover underlying biologic state, and elucidate high-impact genetic modulators of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics, and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience, oncology, and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech, and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com.
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Eric McKeeby
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