I will be starting as a postoc in machine learning at KU Leuven this November, working with Jesse Davies, Wouter Verbeke, and Jente Van Belle.

I completed my Ph.D. in Data Science from the Scuola Normale Superiore in July 2024 advised by Salvatore Ruggieri. As an Early-Stage Researcher with NoBIAS: AI without Bias ITN, I was a recipient of a Marie Skłodowska-Curie Action. I was also a member of the KDD Lab. Previously, I studied Econometrics (M.Sc.) at the Toulouse School of Economics and Economics and History (B.A.) at the University of Florida where I attended as a UWC Scholar. I also worked at Deloitte as a Senior Risk Modeler. Here is my CV.

Broadly, I am interested in data science tools for algorithmic decision-making and its societal implications. My work focuses on the intersection of causal inference, machine learning, and algorithmic fairness. See Google Scholar, dblp, and arXiv for details.

Feel free to reach out at jose[dot]alvarez[at]sns[dot]it.