Amir Sani, PhD


My research interests are in financial and economic time series modeling, simulation and forecasting. My current research focuses on learning forecast combinations and surrogate models.



I teach Machine Learning for Finance and Economics, at the University of Paris II Assas, Ingénierie Statistique Financière.


I am a postdoctoral researcher with Antoine Mandel at the Centre d'Économie de la Sorbonne, Université Paris 1, Panthéon-Sorbonne, Paris School of Economics, where I also organize a biweekly seminar series in Data Driven Economics and Complexity.

My research is part of the European Union Horizons 2020 Future and Emerging Technologies Distributed Global Financial Systems for Society (DOLFINS) project, which addresses the global challenge of making the financial system better serve society.


I completed my PhD, Machine Learning for Decision Making Under Uncertainty, under the supervision of Rémi Munos and Alessandro Lazaric at INRIA-Lille Nord Europe as part of the SequeL team.