Anna Sappington

Anna Sappington aspires to build methods to predict evolutionary events. In particular, she plans to draw connections among machine learning, biology and chemistry to develop reinforcement learning models inspired by evolutionary biology.

Sappington hopes to utilize these improved predictive models to make fundamental discoveries about evolution, as well as to monitor pathogenic outbreaks, and improve targeted cancer treatments. She is a student in the Harvard University-Massachusetts Institute of Technology (MIT) MD-PhD Program, currently in the first year of her doctoral program at MIT in electrical engineering and computer science.

Prior to entering the MD-PhD Program, Sappington received a master’s in machine learning from University College London, and a master’s in genomic medicine from the University of Cambridge, where she studied as a Marshall Scholar. During her time in the United Kingdom, she built structure-informed models of protein-drug interactions, and explored the use of language models to describe T-cell receptor sequence space. In 2019, Sappington received her bachelor’s degree in computer science and molecular biology from MIT, where she was awarded a 2018 Barry M. Goldwater Scholarship, and selected as a Burchard Scholar and an Amgen Scholar.

Born in Annapolis, Maryland, Sappington grew up near the Chesapeake Bay, where she developed a love for nature and a passion for protecting the environment. She has a long record of teaching and mentoring, as demonstrated through her serving as a teaching assistant at MIT, running hackathons and project mentorship initiatives, helping to teach artificial intelligence for social good to thousands of students around the world and serving as a resident tutor at Harvard College. Outside of the lab, Sappington enjoys running along the Charles River, discovering new music and having a warm cup of tea.