Amir Sani



I am a Machine Learning doctoral student supervised by Rémi Munos and Alessandro Lazaric, a
s part of the SequeL Team at INRIA-Lille Nord-Europe, studying risk-averse resource allocation in sequential decision making under uncertainty.

My research interests include adversarial online learning/optimization, decision making under uncertainty, bootstrapping dependent data, imputation, universal compression and graph-based learning methods. My publications include Risk Aversion in Multi-Arm Bandits and Exploiting Easy Data in Online Optimization.

I am particularly interested in the application of machine learning to the study of financial flows in macro-markets.