I am a software engineer at Modal Labs, where I'm designing new abstractions for building data and AI applications in the cloud.

My background is in machine learning and neuroscience. I have been an ML scientist at Flatiron Health, a Simons Fellow at NYU, a PhD student at Stanford, a research assistant at MIT, and an undergrad at Amherst College. My academic work focused on methods for characterizing the functional organization of human brain networks at multiple spatiotemporal scales.

I have also contributed to open source scientific software, most notably through seaborn, a Python data visualization library that I created and maintain.