Asif Khan, PhD

Asif Khan is a Staff Scientist at Harvard Medical School, where he works with Chris Sander on machine learning and AI methods for cancer research and clinical applications. His research interests include representation learning and generative models for large-scale data. His current work is on developing scalable models for longitudinal electronic health records that are robust and well-calibrated for pan-cancer risk stratification. He also works with drug and CRISPR perturbation data to model cellular responses and guide the design of combination therapies. Before joining Harvard, he completed his PhD in Machine Learning at the University of Edinburgh under the supervision of Amos Storkey. His doctoral research focused on geometry for deep representation learning, and he continues to develop geometric methods for the interpretability of large language models. In the Hadlock Lab as a visiting researcher, he implements and evaluates AI models on health data from the Providence cohort.