Matteo Papini
Tenure Track Assistant Professor at Università degli Studi di Milano
Milan, Lombardy, Italy
Summary
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Senior🎓
Top SchoolMatteo Papini is a tenure-track Assistant Professor based in Milan with a decade of experience at the intersection of reinforcement learning research and academic teaching. His trajectory includes a PhD with honors and postdoctoral work focused on RL theory at Universitat Pompeu Fabra, plus a research internship at Facebook, reflecting strong ties between theoretical foundations and industry practice. Matteo has published on reinforcement learning (see his Google Scholar) and has rapidly progressed through roles at Politecnico di Milano to his current faculty appointment at Università degli Studi di Milano. He combines rigorous mathematical training with hands-on experimental work, bridging formal analysis and empirical evaluation. Colleagues value his ability to translate complex RL theory into actionable research agendas and mentoring for early-career researchers. An underappreciated facet is his consistent presence across top European institutions, giving him a broad collaborative network that accelerates translational research.
10 years of coding experience
4 years of employment as a software developer
Dottorato di ricerca, Information Technology, con lode, Dottorato di ricerca, Information Technology, con lode at Politecnico di Milano
Github Skills (12)
deep-reinforcement-learning9
pytorch8
reinforcement-learning8
openai7
deep-learning7
information-theory6
self-organizing-map6
artificial-intelligence4
machine-learning4
python4
incremental-learning3
data-science3
Programming languages (2)
Github contributions (5)
T3p/adaptive-policy-gradient
Dec 2017 - Jan 2019
Contributions:20 commits, 28 pushes, 5 branches in 1 year 1 month
T3p/potion
Dec 2018 - Jan 2025
Policy optimization in pytorch
Contributions:3 PRs, 191 pushes, 6 branches in 6 years 2 months
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