Harry Reyes Nieva is a visiting postgraduate research fellow at Harvard Medical School and PhD student in the Department of Biomedical Informatics at Columbia University, advised by Noémie Elhadad. His research focuses on leveraging machine learning and natural language processing to improve the equity, quality, and safety of health care and support precision medicine. He is especially passionate about using and expanding the vast toolbox that statistical and computational learning offers to better understand, improve, and facilitate study of the health of underserved communities. His PhD is funded by the National Library of Medicine through a Biomedical Informatics and Data Science Research training grant (T15LM007079-28). He is 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).
Prior to pursuing a career in health services research, Mr. Reyes Nieva 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. As Data Quality Assurance Manager for the Nigeria country program, his focus was scale-up and transition of data quality improvement and assurance activities nationwide. In this capacity, he worked closely with in-country quality improvement, monitoring and evaluation, and clinical specialists while developing or modifying pediatric and adult quality improvement dashboards and monitoring and evaluation tools for more than 90,000 patients. His division also produced monitoring and evaluation reports for the U.S. Health Resources and Services Administration (HRSA), U.S. Centers for Disease Control and Prevention (CDC), and United Nations General Assembly Special Session (UNGASS) on HIV/AIDS.
Harry Reyes Nieva graduated from Yale University with a Bachelor of Arts in Sociology and History, studied Population and International Health at the Harvard T.H. Chan School of Public Health, received a Master of Applied Science in Spatial Analysis from the Johns Hopkins Bloomberg School of Public Health, and a Master of Arts in Biomedical Informatics from Columbia University.