About me

I am a PhD candidate in Economics at the University of Southern California.

I specialize in econometric theory. My research projects tackle statistical and optimization problems commonly encountered in causal inference and model-based inference.

I have experience using advanced machine learning methods on large datasets and solving difficult optimization problems. I have helped research teams in industry and academia solve pricing problems, experimental design problems, and portfolio optimization problems.

My CV is available here.

Research interests

• Semi-parametric inference: plug-in estimators and double machine learning; bandwidth selection; kNN and matching estimators; bootstrap for semi-parametric problems.
• Statistical and econometric modeling: inverse problems and identification; inverse problems and misspecification; causal inference as inverse problems.
• Causal inference and experimental design: bridging model-based and design-based causal inference; inference with adaptive experiments; experiments in duopoly.
• Finance and macroeconomics: functional VAR and heterogeneity; robust portfolio optimization; beta strategies.

Education

• Ph.D in Economics, University of Southern California, 2021 -
• M.Sc. in Economic Theory and Econometrics, Toulouse School of Economics, 2019 - 2020
• B.Sc. in Mathematics, University of Paris-Sud, 2015 - 2016
• Grande École - M.Sc. in Management, HEC Paris, 2015 - 2019