I am a data science researcher interested in tools for algorithmic decision-making and their societal implications. Broadly, my work focuses on the intersection of fairness, causal reasoning, and machine learning. See my Google Scholar, dblp, and arXiv for details.
I will start as a postdoc in machine learning at KU Leuven this November.
I completed my Ph.D. in Data Science from the Scuola Normale Superiore, advised by Salvatore Ruggieri. As an Early-Stage Researcher with NoBIAS ITN, I was a recipient of a Marie Skłodowska-Curie Action and a member of the KDD Lab. Previously, I studied Econometrics and Empirical Economics (M.Sc.) at the Toulouse School of Economics, and Economics and History (B.A.), double major, at the University of Florida where I attended as a UWC Scholar. I also worked at Deloitte as a Senior Risk Modeler. See my CV for details.
Reach out at jm[dot]alvarez[dot]colmenares[at]gmail[dot]com.