His research interests include FinTech, household finance and machine learning. His recent work concentrates on robo-advising and the use of Machine Learning techniques to analyze individual investors’ performance, He has worked extensively in analyzing big data, has collaborated with major brokerage houses and asset managers around the world, and has analyzed individual investor performance data. Professor Rossi’s work has been published in leading academic journals such as the Journal of Finance, the Review of Financial Studies, the Journal of Financial Economics and Management Science. Before joining the Smith School, he worked as an economist at the Board of Governors of the Federal Reserve System in Washington DC. He received his PhD in Economics from the University of California, San Diego.