Research

As I mention on my homepage, I am broadly interested in geometric and topological methods for data science and machine learning, with applications to biology.

As an undergrad in the math department at Columbia University, I conducted research at the AlQuraishi Lab, focusing broadly on protein-protein interaction prediction and protein representation problems. I also spent a summer working on an interdisciplinary math modeling project in urban planning, where I led an interdisciplinary group to construct Superblock grid structures across Manhattan (addressing larger concerns with green space and pedestrian/bicyclist safety) using graph clustering and hierarchical partitioning techniques. You can find one of our posters here.

Separately, I am also interested in algebraic topology and homotopy theory – most recently, in rational homotopy theory.

All told, my interests are incredibly varied! But I’m generally curious about how we can use geometric and topological machinery to gain insight into data, systems, and people.