Since March 2021, I am Postdoctoral Researcher at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), in the Artificial Intelligence and Robotic Laboratory (AIRLab) of Politecnico di Milano. In March 2021, I received the Ph.D. in Information Technology at Politecnico di Milano (with honors), defending the dissertation “Exploiting Environment Configurability in Reinforcement Learning”, under the supervision of Prof. Marcello Restelli. In July 2015, I obtained the Bachelor of Science in Computer Engineering at Politecnico di Milano (with honors) and in July 2017, I received the Master of Science in Computer Science and Engineering at Politecnico di Milano (with honors), defending the thesis “Compatible Reward Inverse Reinforcement Learning”. Since November 2021, I am an ELLIS Member.
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My main research interests revolve around Artificial Intelligence and Machine Learning, in particular Reinfocement Learning. I am currently working on reinforcement learning in configurable environments, off-policy reinforcement learning, and inverse reinforcement learning. I am also interested in algorithms, optimization, statistics, probability, and recommendation systems.
I am co-founder of ML cube S.r.l., a Politecnico di Milano spin-off innovative startup, part of Kayrhos Group, providing cutting-edge solutions for Machine Learning Systems and Life-Cycle-Management Optimization.
- Ph.D. in Information Technology, Politecnico di Milano, 2021
- M.Sc. in Computer Science and Engineering, Politecnico di Milano, 2017
- B.Sc. in Engineering of Computing Systems, Politecnico di Milano, 2015
- Winner of “Premio NeoDottori di Ricerca Marco Cadoli 2021” awarded by AIxIA for the best Italian Ph.D. thesis in AI
- Recipient of a “Springer Award”, publication in a Polimi SpringerBriefs volume awarded by DEIB awarded for the best results from the IT PhD program doctors
- Winner of “Premio NeoLaureati Leonardo Lesmo 2018” awarded by AIxIA for the best Italian M.Sc. thesis in AI
- Second place at ACM RecSys Challenge 2017
- 2021-2025: CLINT - CLImate INTelligence: extreme events detection, attribution and adaptation design using machine learning (EU-H2020)