Gabriele Dragotto is the Data X Postdoctoral Fellow at Princeton's Center for Statistics and Machine Learning and a Postdoctoral Research Associate at Princeton's Department of Operations Research and Financial Engineering. He holds a Ph.D. in Mathematics (2022) from Polytechnique Montréal, where he worked at the Canada Excellence Research Chair in Data Science for Real-Time Decision-Making on his thesis "Mathematical Programming Games". He received a B.Sc. in Engineering and Management (2018) from Politecnico di Torino, as part of the project Young Talents. His research is at the interface of mathematical optimization, particularly discrete optimization, game theory, and machine learning. He is broadly interested in improving decision-making when there is plenty of data, competitive interactions, scarce resources, and limited time to make decisions. Gabriele designed several algorithmic and theoretical tools to improve the efficiency of decisions and their social equitability.