Tommaso Cesari

Tommaso Cesari is an Assistant Professor at the School of Electrical Engineering and Computer Science and cross-appointed with the Department of Mathematics and Statistics at the University of Ottawa. He holds a Ph.D. in Computer Science (with distinction) and Master’s/Bachelor’s degrees in Mathematics (summa cum laude) from the University of Milan. His research focuses on theoretical machine learning, online optimization, and algorithmic game theory with applications to digital markets and space operations.

• Education:
  • Bachelor's Degree in Mathematics (summa cum laude), Università degli Studi di Milano (2011)
  • Master's Degree in Mathematics (summa cum laude), Università degli Studi di Milano (2015)
  • Ph.D. in Computer Science (with distinction), Università degli Studi di Milano (2020)

Tommaso’s research spans online learning, regret minimization, and optimization under limited feedback. His work bridges machine learning, game theory, and stochastic optimization, with applications to bilateral trade, market microstructure, and spacecraft operations.

His recent publications emphasize regret analysis in contextual brokerage, market making, and fair bilateral trade. He has contributed to top venues like COLT, NeurIPS, EC, and MOR, often collaborating with researchers such as Nicolò Cesa-Bianchi and François Bachoc.

Tommaso currently teaches ITI 1121 — Introduction to Computing II and CSI 4145 — Machine Learning at the University of Ottawa. He is a member of the ELLIS society and serves as an editor for Springer's Machine Learning Journal.