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Avenue WaySan Diego, CA 92103
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Summary
- Bryan Liang, MD, is a research specialist based in San Diego, CA, with extensive education in chemistry, health policy, and law from high level institutions including MIT, the University of Chicago, and Harvard Law School as well as a medical degree from Columbia University. He has served as a consultant and business accelerator at S-3 Research since 2019 and as a senior advisor at the Global Health Policy Institute since 2014. Previously, he was a professor at the University of California San Diego School of Medicine from 2004 to 2014. His expertise extends to drug supply safety, online health, pharmaceutical policy, and global health policy. His research has been published in high impact factor medical, legal, and policy journals and is frequently cited in the academic and lay press. Liang has also received multiple awards recognizing his mentorship and contributions to education and civic service.
Education & Training
Clarence High SchoolHigh School Dipl. (Hon.), 2014
Harvard Law SchoolJD, Law, 1995
Columbia University Vagelos College of Physicians and SurgeonsClass of 1991
University of ChicagoPhD, Health Policy, 1989
Massachusetts Institute of TechnologyBS, Chemistry, 1983
Certifications & Licensure
HI State Medical License 1993 - 2014
MA State Medical License 1992 - 1996
CT State Medical License 1991 - 1992- SEL, IFR, Complex Aircraft, High Performance AircraftPilot License
Awards, Honors, & Recognition
- Clarence Central Schools Wall of Fame for Professional, Civic, and Humanitarian Service Clarence High School, 2014
- Graduate Student Community Faculty Mentorship Award University of California, San Diego, 2012
- Mentor Recognition Award UCSD School of Graduate Studies, 2008
Publications & Presentations
PubMed
- 39 citationsBig Data, Natural Language Processing, and Deep Learning to Detect and Characterize Illicit COVID-19 Product Sales: Infoveillance Study on Twitter and Instagram.Tim K. Mackey, Jiawei Li, Vidya Purushothaman, Matthew Nali, Neal Shah
JMIR Public Health and Surveillance. 2020-08-25 - 73 citationsMachine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study.Tim K. Mackey, Vidya Purushothaman, Jiawei Li, Neal Shah, Matthew Nali
JMIR Public Health and Surveillance. 2020-06-08 - In Reply—Electronic Health Records and Drugs Prescribed for Off-label IndicationsTim K. Mackey, Bryan A. Liang
Mayo Clinic Proceedings. 2017-04-01
Press Mentions
- Large Language Models and Malpractice RiskDecember 8th, 2023
External Links
- GHPI Websitehttp://www.ghpolicy.org/team/bal/index.html
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