Center for Healthcare AI

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• William Bosl, Scientific Director
• Jeff Hamrick, Senior Director of the Data Institute
• Elisabeth Merkel, Director of Operations
• Victor Palacios, Director of Partnerships
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• Yannet Interian
• Shan Wang
• Diane Woodbridge

• Tobias Loddenkemper, MD, Harvard / BCH, tobias.loddenkemper@childrens.harvard.edu
• Michelle Bosquet Enlow, PhD, Harvard / BCH, michelle.bosquet@childrens.harvard.edu
• Kenneth D. Mandl, MD, Harvard/ BCH, kenneth.mandl@childrens.harvard.edu
• Charles A. Nelson, PhD, Harvard/ BCH, charles.nelson@childrens.harvard.edu
• Kiran Maski, MD, Harvard / BCH, Kiran.Maski@childrens.harvard.edu
• Eric London, MD, Mt. Sinai Hospital, NY, and NY State Institute for Basic Research, naarlondon@gmail.com
• Teguo Daniel, MPH, Global Organization for Health Education and Harvard School of Public Health, teguodjoyum@hsph.harvard.edu
• Lucien Kilonda, Global Organization for Health Education and CEO, Purple Point Neurodiagnostics, lucien@gohealthed.org

The AI & Medicine Initiative was initially funded by Wicklow Capital and previously known as the Wicklow AI Medical Research Initiative (WAMRI).

Jeremy Howard, WAMRI Chairman, Founder Fast.ai
Jeremy Howard is an entrepreneur, business strategist, developer, and educator. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible. He is also a former faculty member at the University of San Francisco, and CSO at doc.ai and platform.ai.

Jeremy’s most recent startup, Enlitic, was the first company to apply deep learning to medicine. He was previously the President and Chief Scientist of the data science platform Kaggle, where he was the top ranked participant in international machine learning competitions 2 years running. He was the founding CEO of two successful Australian startups (FastMail, and Optimal Decisions Group–purchased by Lexis-Nexis). Before that, he spent 8 years in management consulting, at McKinsey & Co, and AT Kearney.

He has many television and other video appearances, including as a regular guest on Australia’s highest-rated breakfast news program, a popular talk on TED.com, and data science and web development tutorials and discussions.

David Uminsky, WAMRI Board Member, former USF Director MS in Data Science & Data Institute, current Executive Director of the Data Science Institute at the University of Chicago
David Uminsky is the former director for the USF MS in Data Science program and Data Institute, and current Executive Director of the Data Science Institute at the University of Chicago. His research interests are in applied mathematics. He is interested in unsupervised machine learning, data clustering, algebraic signal processing, as well as pattern formation, dynamical systems and fluids. David was selected in 2015 by the National Academy of Sciences (NAS) as a Kavli Frontiers of Science Fellow. Each year, 100 researchers under the age of 45 are selected by the academy, and the 20% of the current NAS were previous Kavli Fellows. He is also the founding director of the Bachelor's program in Data Science at  University of San Francisco. Before joining USF, he was a combined National Science Foundation and UC President's Fellow at UCLA, where he was awarded the Chancellor's Award for postdoctoral research. This award is given to approximately top 20 postdocs out of over a thousand who qualify for consideration. He holds a PhD in Mathematics from Boston University and a BS in Mathematics from Harvey Mudd College.

Fred Monroe, Research and Support, Wicklow Capital
Fred Monroe is a machine learning researcher, serial entrepreneur, software developer, trader and investor with over twenty five years of experience working at the forefront of technology.  He is working to apply advances in deep learning and artificial intelligence (AI)  to important real-world problems like those studied at WAMRI.

Fred also works for Wicklow Capital, a family office which makes investments across a wide range of early stage companies. Fred helps Wicklow assess investments and donations, particularly when related to artificial intelligence.