Gianmarco Genalti
Postdoctoral Researcher
Politecnico di Milano
About Me
Gianmarco Genalti is a Postdoctoral Researcher (Contrattista di Ricerca) at the Department of Electronics, Information and Bioengineering (DEIB) of Politecnico di Milano. He received his PhD cum laude in Data Analytics and Decision Sciences from Politecnico di Milano in February 2026, with a thesis titled Multi-Armed Bandits in Dynamic Environments and Heavy-Tailed Rewards. His doctoral studies included a semester as a visiting researcher at the CREST institute of ENSAE in Paris, France. Before pursuing his PhD, he worked as a Data Scientist for Philip Morris International (Switzerland) and ML cube (Italy), developing tools for the dynamic pricing of products. Motivated by these industry applications, his research now bridges theory and practice in multi-armed bandits, online learning, and reinforcement learning, with regular publications in premier conferences like NeurIPS, ICML, COLT, and AISTATS. During his PhD, he also served as an AI research scientist and task leader on several public and industry-funded projects, contributing to ~€1.5 million in institutional funding. He is currently main organizer of the sixth Reinforcement Learning Summer School (RLSS), to be hosted at Politecnico di Milano in June 2026.
Experience
Postdoctoral Researcher (Contratto di Ricerca)- Politecnico di Milano (DEIB) (Milan, Mar 2026 - Present)
Research Programme:Research Programme: Unified Learning from Diverse Human Feedback.
Research Supervisor: Prof. Alberto Maria Metelli
Visiting Researcher - CREST, ENSAE Paris (Paris, Mar 2025 - May 2025)
Research Programme: Learning-Augmented Online Algorithms for Scheduling
Research Supervisor: Prof. Vianney Perchet
Research Fellow (Assegno di Ricerca) - Politecnico di Milano (DIG) (Milan, Jan 2022 - Nov 2022)
Research Programme: Artificial intelligence applications to support process engineering.
Applied Scientist - ML cube (Milan, Mar 2021 - Dec 2021)
Part of a consultancy project for an e-commerce aimed at developing an AI product for the dynamic pricing of 11000+ products.
Data Scientist - Philip Morris International (Lausanne, Aug 2020 - Jan 2021)
Full stack development of an innovative machine learning model based on prices elasticities for sales time series forecasting.
Education
Ph.D. in Data Analytics and Decision Sciences - Politecnico di Milano (Nov 2022 - Feb 2026)
Thesis: Multi-Armed Bandits in Dynamic Environment and Heavy-Tailed Rewards. (Awarded cum laude)
Supervisors: Prof. Nicola Gatti, Prof. Nicolò Cesa-Bianchi
M.Sc. in Mathematical Engineering - Politecnico di Milano (Sep 2019 - Dec 2021)
Main focus: Statistical Learning
Thesis: A Multi-Armed Bandit Approach to Dynamic Pricing
B.Sc. in Mathematical Engineering - Politecnico di Milano (Sep 2016 - Mar 2020)
Thesis: A MiniMax Theorem applications to Machine Learning and Portfolio Optimization
Academic Activities
Main Organizer, 6th Reinforcement Learning Summer School (RLSS 2026) - Politecnico di Milano (Jan 2024 - Jun 2026)
Teaching Assistant, Online Learning and Applications - Politecnico di Milano (2024, 2026)
Teaching Assistant, Statistical Models and Stochastic Processes - Politecnico di Milano (2023, 2024, 2025)