![](/accounts/mgowan/images/aamc-logo.png)
Building AI Partnerships Across Medicine, Industry & Government - September 24
Includes a Live Web Event on 09/24/2024 at 3:00 PM (EDT)
-
Register
- User - Free!
This panel webinar will provide a practical approach to creating AI focused partnerships, including advice, lessons learned, and best practices. Specific examples of how various sized institutions have developed collaborations with industry and government partners to harness the power of AI in medicine will be shared by each panelist, including questions for other institutions to consider when thinking about entering their own partnerships.
![Speaker image](https://4142dfaf7898a80ba7fe-85c4067fd6c098f7db822265073f5412.ssl.cf2.rackcdn.com/aamc_fef1332801abbf15b76821063bd05ceb.jpg)
Jennifer Chow, MBA, MA
Director of External Engagement
Harvard Data Science Initiative
Jennifer Chow is the Director of External Engagement for the Harvard Data Science Initiative. In this role, she leads external strategy for the HDSI. She directs the HDSI’s industry relations through the HDSI Corporate Membership Program, including aligning conversations with the University Development Office, the Office of Technology Development, the Office of Sponsored Programs, and other constituents across Harvard.
Jen brings over a decade of experience in fundraising and development for major research organizations. Prior to joining the HDSI, Jen was Director of Foundation and Corporate Development for Harvard’s Office of the Vice Provost for Research, where she oversaw over $35M in new funding to the university across a broad portfolio of philanthropic gifts and sponsored research grants to faculty. She also advised University leadership on policies related to corporate and foundation partners, establishing new models for engagement.
Jen has also held roles in fundraising and development for the Harvard Faculty of Arts and Sciences, the Broad Institute of MIT and Harvard, and Dana-Farber Cancer Institute. She received her MA in Chemistry from Boston University and her MBA from the Simmons College School of Management, where she was a Forte Fellow and a member of Beta Gamma Sigma.
![Speaker image](https://4142dfaf7898a80ba7fe-85c4067fd6c098f7db822265073f5412.ssl.cf2.rackcdn.com/aamc_a2047902d84c1a5405da1a93935da327.jpg)
Jamie Fairclough, PhD, MPH, MS
Associate Dean and Professor
Roseman University College of Medicine
Dr. Jamie Fairclough is the Associate Dean, Professor, and Director of the Data Science & Engineering Unit at Roseman University College of Medicine in Las Vegas, NV, and an Adjunct Professor of Data Science at Noorda College of Osteopathic Medicine in Provo, UT. At Roseman, she leads a team that implements, leverages, and evaluates scalable data systems, cloud solutions, and artificial intelligence (AI) platforms and prototypes for the medical school. Dr. Fairclough teaches AI, machine learning, epidemiology, and biostatistics courses at the graduate level and pre-college machine learning and epidemiology/disease modeling courses as an instructor at both Stanford University and Johns Hopkins University. She has held academic medicine/pharmacy faculty positions at Florida International University, Florida State University, and Palm Beach Atlantic University, and she previously managed a statewide surveillance system for the Florida Department of Health. Dr. Fairclough received her BS, MPH, and MS degrees from the University of Florida and her PhD degree from Florida State University. She completed an NIH postdoctoral fellowship at Duke University Medical Center as well as additional graduate/postgraduate training in systems engineering (Johns Hopkins), data engineering (University of Chicago), AI and machine learning (University of Texas at Austin), AI engineering (Carnegie Mellon), healthcare AI (Harvard Medical School), business AI and digital leadership (University of Pennsylvania), and systems leadership (Stanford). Most recently, Dr. Fairclough was invited to serve on the FY25 AAMC MedBiquitous Steering Committee, the American Board of Artificial Intelligence in Healthcare, the International Advisory Committee for Artificial Intelligence, and the Royal Statistical Society (UK) AI Task Force.