Welcome! I’m Harry (pronouns: he, him). I’m in the final year of my PhD training in the Department of Biomedical Informatics at Columbia University where I am advised by Noémie Elhadad. For most of my PhD, I was also a Visiting Postgraduate Research Fellow at Harvard Medical School. Recently, I served a 2-year term on the Journal of the American Medical Informatics Association Student Editorial Board and was a co-organizer of the 2023 Machine Learning for Health (ML4H) Symposium. I am also a DAAD AInet Fellow through the German Academic Exchange Service, Deutscher Akademischer Austauschdienst (DAAD).

Building on two decades of domestic and international experience in clinical research and public health informatics, my research focuses on human-centered artificial intelligence (AI) and development of systematic, scalable data-driven approaches to promote health equity. My work usually examines and applies methods such as machine learning, natural language processing, and spatiotemporal analysis in addition to traditional biostatistics and epidemiology. I am particularly interested in using and interrogating multimodal data sources and the vast toolbox that computational learning offers to better understand, improve, and facilitate study of health in populations and communities that are marginalized. Generally, my research can be grouped into four primary domains:

  1. Ethical considerations in AI, clinical practice, and digital health
  2. Promoting health data equity and creating knowledge bases
  3. Elucidating health inequity and creating tools to facilitate further discovery
  4. Enabling equitable learning health systems and precision health

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 training fellowships from 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), a highly competitive honor afforded each year to fewer than a dozen students in the world from disciplines spanning mathematics and astrophysics to chemical engineering and genomics.

I hold a Master of Philosophy and Master of Arts in Biomedical Informatics from Columbia University, Master of Applied Science in Spatial Analysis from the Johns Hopkins Bloomberg School of Public Health, and a Bachelor of Arts in Sociology and History from Yale University.