Research Interests
Drug discoveries have been instrumental in improving global health over the last century, but the median drug now takes about 10 years to bring to market and costs over a billion dollars to develop. My lab aims to expedite the development of precise diagnostics and therapeutics by applying machine learning. Our current work is broadly along two directions. Along the first direction, we use single-cell multiomics to discover regulatory mechanisms governing the interaction between the epigenome, transcription factors, and target genes. This approach relies on methodological innovation, developing new Granger causal inference techniques to capitalize on the “parallax” between simultaneous but separate measures of cell state. In the other direction, we apply large language models to model protein interaction and function. These protein language models enable powerful new approaches to predicting and understanding protein-protein and protein-drug interactions.
Selected Grants
Revealing the hidden topologies of the human kinome
ResearchCollaborator · Awarded by Chan Zuckerberg Initiative · 2023 - 2026Deciphering the Spatio-temporal Causes of Differentiation
ResearchPrincipal Investigator · Awarded by Chan Zuckerberg Initiative · 2024 - 2026The Next Generation of Protein Language Models for Biomolecular Interactions in Health and Disease
ResearchPrincipal Investigator · Awarded by Massachusetts Institute of Technology · 2023 - 2024External Relationships
- martini.ai LLC
This faculty member (or a member of their immediate family) has reported outside activities with the companies, institutions, or organizations listed above. This information is available to institutional leadership and, when appropriate, management plans are in place to address potential conflicts of interest.