Professor Sousa Lobo's research deals with sequential decision making, with a focus on applications that includes revenue management and optimal pricing, as well as market microstructure and optimal trade execution. He also works on methods for the analysis of social networks, in particular the role of affect in intra-organizational task networks. Some of Professor Sousa Lobo's work appears in leading publications such as Operations Research, Journal of Finance, Administrative Science Quarterly, and Harvard Business Review.


Miguel Sousa Lobo holds MS, MA, and PhD degrees from Stanford University, USA, and completed his undergraduate work at Instituto Superior Técnico, Portugal. After two years working with startup companies in Silicon Valley, and prior to joining INSEAD, he held academic appointments at Duke University's Fuqua School of Business and, as visiting professor, at Columbia University's Graduate School of Business.

Sequential Decision-Making; Revenue Management and Price Optimization; Financial Engineering and Market Microstructure; Models for Social Network Analysis.

Uncertainty Data & Judgement; Decision Models.