About Me
Since September 2023, I am a Ph.D. student in Information Technology at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) at Politecnico di Milano, under the supervision of Prof. A.M. Metelli.
In 2021, I received a B.Sc. in Computer Science and Engineering from Politecnico di Milano (with honors), and in 2023, I earned a M.Sc. in Computer Science and Engineering from Politecnico di Milano (with honors), graduating one semester early. During my M.Sc., I attended the prestigious ASP honor program. After graduation and before starting my Ph.D., I worked as a Machine Learning Engineer at ML3.
In my free time, I enjoy sports, particularly skiing ⛷️ and playing tennis 🎾. I competed for three years in the prestigious FITP Serie B and two years in Serie C in Italy, and I am currently an active player in the national circuit.
Download my Curriculum Vitae (updated September 2024).
Research Interests
My research interests lie in the field of Artificial Intelligence and Machine Learning, with a particular focus on Reinforcement Learning. I am currently exploring the theoretical and algorithmic aspects of:
- Inverse Reinforcement Learning
- Reward Learning
Awards and Recognitions
- Oral presentation at ICML 2023 (top 2.39%)
- Ph.D. Scholarship (MIUR)
- Admission to the Alta Scuola Politecnica honour program 2022/2023 - top 90 students of Politecnico di Milano
- "Migliori Matricole" award - best freshmen of Politecnico di Milano 2018/2019
- Scholarship award by Municipality of Romano di L.dia 2018 - best high school students
Publications (updated September 2024)
International Conferences
-
Filippo Lazzati, Mirco Mutti and Alberto Maria Metelli. "How to Scale Inverse RL to Large State Spaces? A Provably Efficient Approach". Advances in Neural Information Processing Systems 38 (NeurIPS), 2024. Acceptance rate: 25.8%. Core 2023: A*.
[arXiv] -
Filippo Lazzati, Mirco Mutti and Alberto Maria Metelli. "Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms". International Conference on Machine Learning 41 (ICML), 2024. Acceptance rate: 2609 /9473 (27.5%). Core 2023: A*.
[Link] [BibTeX] [arXiv] Alberto Maria Metelli, Filippo Lazzati and Marcello Restelli. "Towards Theoretical Understanding of Inverse Reinforcement Learning". International Conference on Machine Learning 40 (ICML), 2023. Acceptance rate: 1827/6538 (27.9%), Oral: 156/6538 (2.39%). CORE 2023: A*.
[Link] [BibTeX] [arXiv]Margherita Musumeci, Juan Sebastian Amaya Cano, Filippo Lazzati, Chiara Martano, Francesco Pappone, Claudio Ramonda, Marco Ricci, Jorge A. Tobon, Giovanna Turvani, Mario R. Casu, Marco Mussetta, and Francesca Vipiana. "Development of a Deep-Learning Pipeline to Detect and Locate Contaminants of Industrial Products via non-Invasive Microwave Signals". IEEE Conference on AgriFood Electronics (IEEE CAFE), 2023.
[Link] [BibTeX]
Pre-prints
-
Filippo Lazzati and Alberto Maria Metelli. "Learning Utilities from Demonstrations in Markov Decision Processes".
[arXiv]
Education
Ph.D. in Information Technology (Sep 2023 - Now)
Focus on Inverse Reinforcement Learning and Reward
Learning
Duration: 3 years
Where: Politecnico di Milano, Milan, Italy
Supervisor: Prof. Alberto Maria Metelli
Alta Scuola Politecnica (ASP) Diploma (Mar
2022 - Feb 2024)
Multidisciplinary honour program - ASP website
Duration: 2 years
Where: Politecnico di Milano, Milan, Italy
Project: Microwave sensing for food
contamination monitoring - Wavision
[Link
paper]
[PDF paper]
M.Sc. in Computer Science and Engineering (Sep 2021 - May 2023)
Duration: 2 years
Where: Politecnico di Milano, Milan, Italy
Final mark: 110 cum laude/110
Average exam mark: 29.80/30
[Link
thesis]
[PDF thesis]
B.Sc. in Computer Science and Engineering
(Sep 2018 - Jul 2021)
Duration: 3 years
Where: Politecnico di Milano, Milan, Italy
Final mark: 110 cum laude/110
Average exam mark: 29.97/30
High School Diploma (Sep 2013 - Jun 2018)
Liceo scientifico - scienze
applicate
Duration: 5 years
Where: Istituto Superiore don Lorenzo Milani, Romano di Lombardia, Italy
Final mark: 100/100
Experience
Machine Learning Engineer (Feb 2023 -
Jul 2023)
Development of reinforcement learning and machine learning
algorithms in Python
Duration: 6 months
Company: ML Cube srl
Type of employment: internship
Type of business or sector: IT Services and IT Consulting
Information Technology Teacher (Oct 2019 -
Feb 2020)
Teaching the fundamentals of Windows, Internet, and
the Microsoft Office Suite
Duration: 5 months
Company: Municipality of Romano di Lombardia
Type of employment: Fixed Term Contract
Type of business or sector: Public Sector, Teaching
Academic Activities
Teaching
Lab Sessions Lecturer (Sep 2024 - Dec
2024)
Lab sessions on C and Matlab programming
languages
University: Politecnico di Milano
Duration: 18 hours
Course: Fondamenti di Informatica
Participation to International Conferences and Workshops
International Conference on Machine Learning - ICML 2024
Vienna, Austria. July 2024.
European Workshop on Reinforcement Learning - EWRL 2023
Brussels, Belgium. September 2023.
Master's Students Supervision
Leonardo Pesce. Co-supervision. (M.Sc. in Computer Science and Engineering, in progress)
Reviewing
Reviewer for International Conferences:
Neural Information Processing Systems (NeurIPS)
International Conference on Machine Learning (ICML)
International Conference on Learning Representations (ICLR)
Reviewer for International Journals:
TMLR - Transactions on Machine Learning Research (Q1)
IEEE - Transactions on Neural Networks and Learning Systems (Q1)
Reviewer for International Workshops:
ARLET @ ICML 2024
Contacts
Email
filippo.lazzati@polimi.it
Office
Office 21, First Floor of Building 21
Dipartimento di Elettronica, Informazione e Bioingegneria
Politecnico di Milano
Via Ponzio 34/5, Milan, 20133, Italy