After the Algorithm: Making Machine Learning Work in Healthcare

Lecture | January 17 | 3-4 p.m. | Genentech Hall, UCSF, Genentech Hall Room N114

 600 16th St, San Francisco, CA 94158

 Leonard D’Avolio, Brigham and Women’s Hospital, Harvard Medical School, Cyft

 Berkeley Institute for Data Science, UCSF Bakar Computational Health Sciences Institute

Abstract: In his talk, titled "After the Algorithm: Making Machine Learning Work for Healthcare," Leonard D'Avolio, Ph.D. shares lessons learned from 15 years of experience designing, developing, and deploying machine learning-enabled systems in academic, government, philanthropic, and industrial healthcare environments. This talk is a painfully honest view of the promise and potential of machine learning in healthcare as well as the cultural, economic, and practical barriers that stand in its way. As the title suggests, Dr. D'Avolio's primary interest is preparing students, entrepreneurs, data scientists, managers, and executives for what really matters - what comes after the algorithm.

Leonard D’Avolio, Ph.D. helps government, academia, philanthropy, and industry use data to improve healthcare, with a particular focus on machine learning. He’s the co-founder of Cyft, a healthcare analytics company, and an Assistant Professor at Brigham and Women’s Hospital and Harvard Medical School. He serves as an advisor to the Helmsley Charitable Trust Foundation and several healthcare startups and is a board member for Youth Development Organization in Lawrence, Massachusetts. His work has been funded by several institutions including the National Cancer Institute, Department of Veterans Affairs, Department of Defense, Bill and Melinda Gates Foundation, National Library of Medicine, and the Helmsley Charitable Trust Foundation. His straightforward and practical advice on using data to improve healthcare has made him an internationally sought-after speaker and his writing and research are routinely featured in academic and industry publications.

 bids@berkeley.edu