I am a third year Ph.D. student in Computer Science at Cornell University. I am broadly interested in building accountable, robust distributed machine learning systems with theoretical guarantees. This work lives at the intersection of machine learning and distributed computing: I investigate how consistency, staleness, and concurrency control considerations impact the behavior of machine learning algorithms. I am very fortunate to be advised by Chris De Sa. You can find my CV here.
Prior to attending Cornell, I worked for several years in industry at companies both big and small. I graduated summa cum laude from Columbia University, where I studied Computer Science and Archaeology and was elected to Phi Beta Kappa.
I care very deeply about the impact of my work, specifically its legal and social implications. I am a member of Cornell's initiative on Artifical Intelligence, Policy, and Practice and am engaged in a variety of outreach and service programs in Computer Science mentorship and education.
In my free time, I am fully committed to perfecting the art of rolling fresh pasta. I am usually doing that, but if not you can find me reading, at the gym, learning Italian, or working on my practice of foolishness / being a menace.
Credit: Meghan Witherow