Thematic Session 21

THEMATIC SESSION #21

Simone Barcellona

Polytechnic of Milan, Italy

• Simone.barcellona@polimi.it

Loris Cannelli

Dalle Molle Institute for Artificial Intelligence, Switzerland

• loris.cannelli@idsia.ch

Christian Laurano

Polytechnic of Milan, Italy

• christian.laurano@polimi.it

Gabriele Maroni

IDSIA - Dalle Molle Institute for Artificial Intelligence, USI/SUPSI, Lugano, Switzerland

• gabriele.maroni@supsi.ch

The integration of Artificial Intelligence (AI) is revolutionizing industries across the globe, driving innovation and operational efficiency. This session explores the transformative role of AI in reshaping various industrial sectors. By enabling smarter manufacturing, optimizing supply chains, and enhancing product design, AI is becoming a cornerstone of modern industrial practices. As examples, key AI applications in the new industrial era can be energy storage systems (batteries, supercapacitors,...) , electric vehicle (EV) technologies, demonstrating how AI is enhancing performance, sustainability, and energy efficiency.

Furthermore, the session will delve into the impact of AI on Industry 5.0, where human-machine collaboration is pivotal for more personalized and agile manufacturing processes.

Topics of interest for this Special Session include but are not limited to:

• AI for industry applications;
• Human-machine collaboration;
• Industry 5.0;
• Supercapacitor modeling;
• Integrated AI Electric vehicles;
• Machine learning and Data-Driven techniques for batteries parameters estimation;
• Functional safety for the BMS and battery packs;
• Energy storage systems integration and management;
• Battery management strategies for EVSs.

Simone Barcellona was born in Milan (Italy), in May 1985. He received the M.Sc. and Ph.D. degrees in electrical engineering from the Politecnico di Milano, Milan, Italy in July 2011 and December 2014, respectively. During the PhD studies, the research activity was mainly devoted to the study of the theoretical and mathematical topology and operation of power static converters and the study of conservative functions relating to the switching networks where the converters are a cause. Currently, he is a researcher at the Politecnico di Milano. His current research interests include the study of power electronic converters and modeling of energy storage systems.

Loris Cannelli received his B.S. in Electrical and Telecommunication Engineering from the University of Perugia, Italy, his M.S. in Electrical Engineering from the State University of New York at Buffalo, NY, and his Ph.D. in Industrial Engineering from the Purdue University, West Lafayette, IN, USA. Since 2019, he has been a researcher at IDSIA/SUPSI in Lugano, Switzerland, and his main interests revolve around applying machine learning and artificial intelligence techniques to multi-agent optimization problems.

Christian Laurano was born in Lodi, Italy in 1990. He received the M.Sc. and Ph.D. degrees (cum laude) in electrical engineering from the Politecnico di Milano, Milan, Italy, in 2014 and 2018, respectively. From 2018 to 2020, he was a Post-Doctoral Researcher with the Politecnico di Milano. From 2020 to 2021, he was with the Measurement and Diagnostic Group, Transmission and Distribution Technology Department, RSE SpA. He is currently an Associate Professor with the Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano. His main research interests include innovative methods to model and characterize electrical transducers, diagnostic techniques devoted to electrical grid components, and power quality monitoring.

Gabriele Maroni received the Master Degree in Computer Science Engineering cum laude in 2016 and the Ph.D. in Engineering and Applied Sciences in 2019 both from Università degli Studi di Bergamo. In 2016 he worked as Data Scientist at Reply S.p.A. (MIlano, Italy), from October 2019 to November 2021 he worked as Machine Learning Engineer at Tenaris S.A. (Dalmine, Italy). Since November 2021 he is Researcher at IDSIA - Dalle Molle Institute for Artificial Intelligence (Lugano, Switzerland). He has years of experience working on both theoretical and applied research focused on Machine Learning and Control Theory techniques applied to interdisciplinary sectors such as Financial, Biomedical and Manufacturing.