Learning the Learners: A Meta-Learning Approach for System Identification
Event details
| Date | 10.02.2026 |
| Hour | 14:00 › 15:30 |
| Speaker | Prof Dario Piga Professor at the SUPSI–IDSIA Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland. Dr Marco Forgione, Senior Researcher, IDSIA Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland. |
| Location | |
| Category | Conferences - Seminars |
| Event Language | English |
Abstract:
In recent years, system identification has greatly benefited from machine learning, particularly for modeling complex, nonlinear dynamical systems with partially unknown physics. However, learning black-box models with standard approaches often requires large datasets and substantial computational resources. This talk explores meta-learning as a promising alternative. Rather than relying on manually designed system identification algorithms, we use meta-learning techniques to learn the learning procedure itself from a collection of datasets, so that it is optimally adapted to an entire class of problems.
Biography:
Dario Piga is a Professor at the SUPSI–IDSIA Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland, and the founder and head of the LEarning for Optimization and coNtrol (LEON) group at IDSIA. His main research interests include system identification, control theory, machine learning, and nonlinear optimization. He has served as Principal Investigator on several research projects in collaboration with international industry partners, focusing on the development of innovative AI-based and control systems for applications in manufacturing, transportation, and the biomedical and chemical sectors. He has served as a member of the Conference Editorial Board of the IEEE Control Systems Society (2018–2025) and of the Conference Editorial Board of the European Control Association (2020–2025). He is currently an Associate Editor of the IFAC journal Automatica and Chair of the IEEE-CSS Technical Committee on System Identification and Adaptive Control.
Marco Forgione received his M.Sc. degree in Computer Engineering from the University of Pavia, Italy, in 2009, and his Ph.D. degree in Systems and Control Engineering from the Delft University of Technology, The Netherlands, in 2014. He was a Postdoctoral Researcher at École Centrale de Lyon, France, from 2014 to 2015, and subsequently an R&D Control Engineer at Whirlpool EMEA, Italy, from 2015 to 2018. He is currently a Senior Researcher at the IDSIA Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland. His research interests lie at the intersection of machine learning, system identification, and automatic control.
In recent years, system identification has greatly benefited from machine learning, particularly for modeling complex, nonlinear dynamical systems with partially unknown physics. However, learning black-box models with standard approaches often requires large datasets and substantial computational resources. This talk explores meta-learning as a promising alternative. Rather than relying on manually designed system identification algorithms, we use meta-learning techniques to learn the learning procedure itself from a collection of datasets, so that it is optimally adapted to an entire class of problems.
Biography:
Dario Piga is a Professor at the SUPSI–IDSIA Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland, and the founder and head of the LEarning for Optimization and coNtrol (LEON) group at IDSIA. His main research interests include system identification, control theory, machine learning, and nonlinear optimization. He has served as Principal Investigator on several research projects in collaboration with international industry partners, focusing on the development of innovative AI-based and control systems for applications in manufacturing, transportation, and the biomedical and chemical sectors. He has served as a member of the Conference Editorial Board of the IEEE Control Systems Society (2018–2025) and of the Conference Editorial Board of the European Control Association (2020–2025). He is currently an Associate Editor of the IFAC journal Automatica and Chair of the IEEE-CSS Technical Committee on System Identification and Adaptive Control.
Marco Forgione received his M.Sc. degree in Computer Engineering from the University of Pavia, Italy, in 2009, and his Ph.D. degree in Systems and Control Engineering from the Delft University of Technology, The Netherlands, in 2014. He was a Postdoctoral Researcher at École Centrale de Lyon, France, from 2014 to 2015, and subsequently an R&D Control Engineer at Whirlpool EMEA, Italy, from 2015 to 2018. He is currently a Senior Researcher at the IDSIA Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland. His research interests lie at the intersection of machine learning, system identification, and automatic control.
Practical information
- General public
- Free