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Brero, G.,Eden, A.,Chakrabarti, D.,Gerstgrasser, M.,Li, V.,Greenwald, A.,Parkes, D., Stackelberg POMDP: A Reinforcement Learning Approach for Economic Design, .

Brero, G.,Lubin, B.,Seuken, S., Machine Learning-powered Iterative Combinatorial Auctions., .

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., .

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.

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 Ë¿¹ÏÊÓƵ, 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 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.