Keynote Speaker

Hamid Reza Karimi, Politecnico di Milano, Italy  

Hamid Reza Karimi is Professor of Applied Mechanics with the Department of Mechanical Engineering, Politecnico   di   Milano,  Milan, Italy and the Honorary Visiting Professor within the School of Computing & Engineering at the University of Huddersfield, UK. Prof. Karimi’s original research and development achievements span a broad spectrum within the topic of automation/control systems, and intelligence systems with applications to complex systems such as wind turbines, vehicles, robotics and mechatronics. Prof. Karimi is an ordinary Member of Academia Europaea (MAE), Honorary Academic Member of National Academy of Sciences of Bolivia, Distinguished Fellow of the International Institute of Acoustics and Vibration (IIAV), Fellow of The International Society for Condition Monitoring (ISCM), Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA), Member of Agder Academy of Science and Letters and also a member of the IFAC Technical Committee on Mechatronic Systems, the IFAC Technical Committee on Robust Control, the IFAC Technical Committee on Automotive Control as well as member of the board of Directors of The International Institute of Acoustics and Vibration (IIAV). Prof. Karimi is the recipient of the 2021 BINDT CM Innovation Award, the Web of Science Highly Cited Researcher in Engineering, the 2020 IEEE Transactions on Circuits and Systems Guillemin-Cauer Best Paper Award, August-Wilhelm-Scheer Visiting Professorship Award, JSPS (Japan Society for the Promotion of Science) Research Award, and Alexander-von-Humboldt-Stiftung research Award, for instance. Prof. Karimi is currently the Editor-in-Chief of the Journal of Cyber-Physical Systems, Subject Editor, Technical Editor or Associate Editor for some international  journals and Book Series Editor for Springer, CRC Press and Elsevier. He has also participated as General Chair, keynote/plenary speaker, distinguished speaker or program chair for several international conferences in the areas of Control Systems, Robotics and Mechatronics.

Speech Title: Intelligent Soft Sensing and Prediction for Industrial Applications

In this speech, we explore innovative methodologies for efficient and cost-effective process optimization in industrial applications. Soft sensing refers to approximating hard-to-measure variables using easily measurable ones at a given instant, whereas prediction extends the focus to future horizons. This presentation highlights several novel soft sensing and prediction frameworks developed for two specific case studies: industrial aluminum electrolysis and undermining systems. These frameworks leverage semi-supervised and self-supervised learning to address few-shot labeled sample scenarios while maintaining performance integrity. The talk concludes with key insights and future directions.