I'm currently a staff data scientist at Lyft where my research focuses on using causal inference and machine learning to optimize policy in a scalable way.

I'm also an adjunct professor of data science at Columbia University, where I"m teaching a course on using data science in industry.

I completed my PhDs at the Courant Institute (NYU) and UPMC (Paris VI) (thesis link: here) and worked full time as a research-only fellow and instructor of mathematics at DPMMS at the University of Cambridge. I have worked in Germany, France, England and the USA over the past several years while completing my degrees and have gained considerable experience in variational methods, differential equations and applied analysis.