I work as a Staff Applied Scientist at Lyft in New York where I focus on problems at the intersection of causal inference, experimentation and machine learning. From 2017-2019 I was an adjunct professor of Data Science at Columbia University, where I taught the course Introduction to Data Science in Industry .
Prior to entering industry, I was a Herchel Smith Research Fellow in Mathematics at The University of Cambridge, where I worked on problems related to energy driven pattern formation in mathematical physics and its connections to geometric measure theory. I completed my PhD at the Courant Institute of Mathematical Sciences and Paris VI UPMC where I specialized in Nonlinear PDE and Calculus of Variations. Click here for a copy of my thesis (NYU version).
06-Dec-2023Room 1A12Unlocking the Power of Causal Inference: Going Beyond AI to optimize decisions