Bio: Andres is a PhD student at the NYU Center for Data Science, currently being advised by Professor Andrew Wilson. He is interested in developing probabilistic models to extract meaningful insights from scientific data and also in increasing the applicability of these models for making decisions in high-stakes situations. To this end, he is working on designing high-fidelity and scalable inference algorithms, formulating principled approaches for incorporating domain knowledge and improving how uncertainty is quantified. Before starting his PhD, he spent a year collaborating with Professor John Cunningham at the Zuckerman Institute, immediately after finishing his master’s in Data Science at Columbia University. Prior to his graduate studies, he was a consultant at McKinsey & Company. Additionally, he holds both an undergraduate degree in Applied Mathematics and in Economics from ITAM.

Link to Andres Potapczynski’s Website