Info
Assistant Professor of Information Systems and Analytics
Gianluca Brero
Gianluca Brero is an Assistant Professor of Information Systems and Analytics at 91È«ÄÜ´óÉñ University. Before joining Bryant, he was a Postdoctoral Fellow at Brown and Harvard, hosted by Amy Greenwald and David Parkes, respectively.
Gianluca earned his Ph.D. in Computer Science from the University of Zurich in 2020 under the guidance of Sven Seuken. During his doctoral studies, he interned at Microsoft Research – New York City, advised by Sébastien Lahaie.
Before his Ph.D., Gianluca earned a double Master's degree in Mathematics and Innovation (Alta Scuola Politecnica) from Turin Polytechnic and Milan Polytechnic and a Bachelor's degree in Mathematics from Turin Polytechnic.
Gianluca received all of his degrees with the highest honors (summa cum laude) and was recognized by Turin Polytechnic as the top mathematics graduate of his academic year.
Gianluca earned his Ph.D. in Computer Science from the University of Zurich in 2020 under the guidance of Sven Seuken. During his doctoral studies, he interned at Microsoft Research – New York City, advised by Sébastien Lahaie.
Before his Ph.D., Gianluca earned a double Master's degree in Mathematics and Innovation (Alta Scuola Politecnica) from Turin Polytechnic and Milan Polytechnic and a Bachelor's degree in Mathematics from Turin Polytechnic.
Gianluca received all of his degrees with the highest honors (summa cum laude) and was recognized by Turin Polytechnic as the top mathematics graduate of his academic year.
Degrees Awarded
Ph D, University of Zurich
M Sc, Politecnico di Milano and Politecnico di Torino
B Sc, Politecnico di Torino
Ph D, University of Zurich
M Sc, Politecnico di Milano and Politecnico di Torino
B Sc, Politecnico di Torino
Selected Publications
Brero, G., Lubin, B., Seuken, S., Machine Learning-powered Iterative Combinatorial Auctions., Management Science.
Gerstgrasser, M., Brero, G., Eden, A., Chakrabarti, D., Lepore, N., Li, V., Mibuari, E., Greenwald, A., Parkes, D., Stackelberg POMDP: Learning to Lead via Reinforcement Learning, Journal of Artificial Intelligence Research (JAIR).
Kulkarni, R., Brero, G., Ding, Y., Gupta, S., Koenig, S., Krishnan, R., Serra, T., Vayanos, P., Wasserkrug, S., Wiberg, H., Making a Case for Research Collaboration Between Artificial Intelligence and Operations Research Experts, Workshop report published by the Computing Research Association (CRA).
Lubin, B., Beyeler, M., Brero, G., Seuken, S., iMLCA: Machine Learning-powered Iterative Combinatorial Auctions with Interval Bidding, .
Mibuari, E., Brero, G., Parkes, D., Learning to Mitigate AI Collusion in Electricity Markets., .
Nambiar, H., Boonbandansook, W., Greenwald, A., Edmonds, R., Brero, G., Lubin, B., Risk-Aware Market Clearing in Electricity Markets, .
Paul, L., Arnold, Q., Brero, G., Fast Iterative Combinatorial Auctions via Deep Reinforcement Learning, .
Edmonds, R., Goktas, D., Brero, G., Greenwald, A., Building Auctions from Fair Division Mechanisms, Games, Agents, and Incentives Workshop (GAIW) at AAMAS 2025, 2025.
Brero, G., Mibuari, E., Lepore, N., Parkes, D., Learning to Mitigate AI Collusion on Economic Platforms, Proceedings of the Thirty-Sixth Conference on Neural Information Processing Systems,, 2022.
Beyeler, M., Brero, G., Lubin, B., Seuken, S., iMLCA: Machine Learning-powered Iterative Combinatorial Auctions with Interval Bidding, Proceedings of the 22nd ACM Conference on Economics and Computation, 2021.
Brero, G., Eden, A., Gerstgrasser, M., Parkes, D., Rheingans-Yoo, D., Reinforcement Learning of Sequential Price Mechanisms, Proceedings of the Thirty-fifth AAAI Conference on Artificial Intelligence , 2021.
Brero, G., Lahaie, S., Seuken, S., Fast Iterative Combinatorial Auctions via Bayesian Learning., Proceedings of the Thirty-third AAAI Conference on Artificial Intelligence (AAAI-19), 2019.
Brero, G., Lubin, B., Seuken, S., Combinatorial Auctions via Machine Learning-based Preference Elicitation, Proceedings of the Twenty- seventh International Joint Conference on Artificial Intelligence and the Twenty- third European Conference on Artificial Intelligence (IJCAI-ECAI-18),, 2018.
Brero, G., Lahaie, S., A Bayesian Clearing Mechanism for Combinatorial Auctions, Proceedings of the Thirty-second AAAI Conference on Artificial Intelligence, 2018.
Brero, G., Lubin, B., Seuken, S., Probably Approximately Efficient Combinatorial Auctions via Machine Learning, Proceedings of the Thirty- first AAAI Conference on Artificial Intelligence, 2017.
Brero, G., Como, G., Fagnani, F., Dynamics in network games with local coordination and global congestion effects, Proceedings of the Fifty-third IEEE Conference on Decision and Control (CDC-14), 2014.
Magnanelli, E., Brero, G., Espinoza Garnier, R. V., Mazzoletti, G., Rizzi, A. M., Comai, S., HaptiChem: Haptic and Visual Support in Interactions with the Microscopic World, Springer International Publishing, 2014.
Brero, G., Lubin, B., Seuken, S., Machine Learning-powered Iterative Combinatorial Auctions., Management Science.
Gerstgrasser, M., Brero, G., Eden, A., Chakrabarti, D., Lepore, N., Li, V., Mibuari, E., Greenwald, A., Parkes, D., Stackelberg POMDP: Learning to Lead via Reinforcement Learning, Journal of Artificial Intelligence Research (JAIR).
Kulkarni, R., Brero, G., Ding, Y., Gupta, S., Koenig, S., Krishnan, R., Serra, T., Vayanos, P., Wasserkrug, S., Wiberg, H., Making a Case for Research Collaboration Between Artificial Intelligence and Operations Research Experts, Workshop report published by the Computing Research Association (CRA).
Lubin, B., Beyeler, M., Brero, G., Seuken, S., iMLCA: Machine Learning-powered Iterative Combinatorial Auctions with Interval Bidding, .
Mibuari, E., Brero, G., Parkes, D., Learning to Mitigate AI Collusion in Electricity Markets., .
Nambiar, H., Boonbandansook, W., Greenwald, A., Edmonds, R., Brero, G., Lubin, B., Risk-Aware Market Clearing in Electricity Markets, .
Paul, L., Arnold, Q., Brero, G., Fast Iterative Combinatorial Auctions via Deep Reinforcement Learning, .
Edmonds, R., Goktas, D., Brero, G., Greenwald, A., Building Auctions from Fair Division Mechanisms, Games, Agents, and Incentives Workshop (GAIW) at AAMAS 2025, 2025.
Brero, G., Mibuari, E., Lepore, N., Parkes, D., Learning to Mitigate AI Collusion on Economic Platforms, Proceedings of the Thirty-Sixth Conference on Neural Information Processing Systems,, 2022.
Beyeler, M., Brero, G., Lubin, B., Seuken, S., iMLCA: Machine Learning-powered Iterative Combinatorial Auctions with Interval Bidding, Proceedings of the 22nd ACM Conference on Economics and Computation, 2021.
Brero, G., Eden, A., Gerstgrasser, M., Parkes, D., Rheingans-Yoo, D., Reinforcement Learning of Sequential Price Mechanisms, Proceedings of the Thirty-fifth AAAI Conference on Artificial Intelligence , 2021.
Brero, G., Lahaie, S., Seuken, S., Fast Iterative Combinatorial Auctions via Bayesian Learning., Proceedings of the Thirty-third AAAI Conference on Artificial Intelligence (AAAI-19), 2019.
Brero, G., Lubin, B., Seuken, S., Combinatorial Auctions via Machine Learning-based Preference Elicitation, Proceedings of the Twenty- seventh International Joint Conference on Artificial Intelligence and the Twenty- third European Conference on Artificial Intelligence (IJCAI-ECAI-18),, 2018.
Brero, G., Lahaie, S., A Bayesian Clearing Mechanism for Combinatorial Auctions, Proceedings of the Thirty-second AAAI Conference on Artificial Intelligence, 2018.
Brero, G., Lubin, B., Seuken, S., Probably Approximately Efficient Combinatorial Auctions via Machine Learning, Proceedings of the Thirty- first AAAI Conference on Artificial Intelligence, 2017.
Brero, G., Como, G., Fagnani, F., Dynamics in network games with local coordination and global congestion effects, Proceedings of the Fifty-third IEEE Conference on Decision and Control (CDC-14), 2014.
Magnanelli, E., Brero, G., Espinoza Garnier, R. V., Mazzoletti, G., Rizzi, A. M., Comai, S., HaptiChem: Haptic and Visual Support in Interactions with the Microscopic World, Springer International Publishing, 2014.
Awards and Honors
Merit Award, 2026
Merit Award, 2026
Teaching Interests
Gianluca Brero’s teaching interests lie in market design, machine learning, and data and AI ethics. Before joining Bryant University, he taught courses on game theory and market design at the University of Zurich, and on data and AI ethics at Brown University. At 91È«ÄÜ´óÉñ, Dr. Brero is deeply involved in AI-related teaching, offering courses in deep learning, AI ethics and governance, and statistics. His teaching aims to equip students with the technical and ethical foundations needed to harness the power of AI for positive social impact.
Gianluca Brero’s teaching interests lie in market design, machine learning, and data and AI ethics. Before joining Bryant University, he taught courses on game theory and market design at the University of Zurich, and on data and AI ethics at Brown University. At 91È«ÄÜ´óÉñ, Dr. Brero is deeply involved in AI-related teaching, offering courses in deep learning, AI ethics and governance, and statistics. His teaching aims to equip students with the technical and ethical foundations needed to harness the power of AI for positive social impact.
Research Interests
Gianluca Brero is dedicated to researching and optimizing economic platforms. His primary focus lies in domains such as electricity trading, spectrum auctions, and supply chains, with the goal of enhancing their efficiency and ensuring equitable resource allocation.
Gianluca Brero is dedicated to researching and optimizing economic platforms. His primary focus lies in domains such as electricity trading, spectrum auctions, and supply chains, with the goal of enhancing their efficiency and ensuring equitable resource allocation.
Professional Memberships
Institute for Operations Research and the Management Sciences
Institute for Operations Research and the Management Sciences