Welcome! I’m Harry (pronouns: he, him), a PhD candidate in the Department of Biomedical Informatics at Columbia University, advised by Noémie Elhadad, and a Visiting Postgraduate Research Fellow in Medicine at Harvard Medical School. Recently, I served a 2-year term on the Journal of the American Medical Informatics Association Student Editorial Board. I am also a co-organizer of the Machine Learning for Health (ML4H) Symposium this year and chair the Author Mentorship Program.

Building on my background in clinical research and public health practice, my research examines and applies methods such as machine learning, deep learning, natural language processing, and spatial analysis to monitor, evaluate, and enable equitable learning health systems and support precision health. In particular, my primary interests center around using and interrogating multimodal data sources and the vast toolbox that computational learning offers to better understand, improve, and facilitate the study of health in populations and communities that are marginalized.

As a first generation college graduate, I have benefitted greatly from many excellent mentors in my academic and personal journey. I am also an active mentor/mentee of the Biomedical Science Careers Program. Before starting my PhD program, I held a number of positions at Brigham and Women’s Hospital (BWH), Harvard Medical School (HMS), and the Harvard T.H. Chan School of Public Health (HSPH). While at BWH and HMS, I served on more than a dozen research studies and pursued my own projects with generous support from Harvard Catalyst. Prior to pursuing a career in biomedical informatics and health services research, I was a member of the Strategic Information division of the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) at Harvard University which aimed to rapidly expand antiretroviral therapy (ART) treatment and care programs for people living with HIV/AIDS in sub-Saharan Africa.

My PhD is funded by the National Library of Medicine (NLM) and National Institute of Allergy and Infectious Diseases (NIAID) through a Biomedical Informatics and Data Science Research training grant (T15LM007079). I am also the recipient of a Computational and Data Science Fellowship from the Association for Computing Machinery (ACM) Special Interest Group in High Performance Computing (SIGHPC).