I hold a Ph.D. in Economics, with a joint degree in Statistics, from the University of Michigan.
I work at the intersection of causal inference (CI), particularly with observational data, and machine learning (ML). In my research, I: (1) leverage ML to capture complex confounding variation, making CI estimation feasible in high-dimensional settings; and (2) apply CI principles to detect discrimination in ML models, while also developing tools to address other Responsible AI challenges.
Many of my projects stem from applied problems that push the boundaries of existing statistical methods, inspiring the creation of new methodologies. I often illustrate these methods through applications aimed at promoting social fairness.
I am Research Fellow at the Institute for Applied Economic Research within the Brazilian government (IPEA).
Previously, I was a Data Science & AI Research Fellow at the Michigan Institute for Data and AI in Society (MIDAS), and a Responsible AI Research Fellow for the Rocket Companies.