I am a Research Scientist Manager on the Core Data Science team at Meta. My research interests lie in the fields of machine learning and data mining. In particular, I focus on the development of algorithms which leverage the structure of graphs to make predictions, such as graph propagation algorithms or graph representation learning. I am also interested in graph matching, entity resolution and clustering and have a general interest in understanding human patterns and improving transportation and urbanism. I work with various teams across Meta to deploy the algorithms at scale. Our goal is to provide people with a more meaningful experience online through a better understanding of how people connect to each other and to their environment, as well as to detect abuse to keep people safe online. For this reason, we focus on models with interpretable results and/or assumptions.
I received a PhD in electrical engineering and computer science from the University of California, Berkeley where I studied statistical models of queuing networks using mobile data under the supervision of Alexandre Bayen (CEE-EE) and Pieter Abbeel (EE-CS). Before that, I did my undergrad and MS in applied mathematics at the Ecole Polytechnique, France. I also received a PhD and a MS in transportation engineering from Ecole des Ponts ParisTech.
Location-based services, mobile data, modeling, convex optimization, data visualization, and statistical learning