Plenary Speeches

Plenary Speech I

Multiscale Intelligent Learning under Cross-scale Uncertainties for Manufacturing

Professor Han-Xiong Li
City University of Hong Kong, Hong Kong

The industrial manufacturing encompasses a variety of production equipment and processes: from single mechanical actions to multiple nested operations, complex production scheduling, and ultimately, intelligent management decisions. The manufacturing process can be viewed as a multi-variables coupled, multi-scale complex system (including fast/slow time scales, space/time scales, etc.). The cumulative errors of distributed operations generate multi-scale and even cross-dimensional uncertainties, which is a key challenge for intelligent manufacturing.

From an engineering perspective: achieving control requires first decomposing the complexity of the process, and then manipulating the specific characteristics of the decomposed components at different levels, including system design (static control), process modeling and control (dynamic control), and data learning and decision-making (intelligent control). From an academic perspective, this is a complex system engineering problem.

Just as quantum physics has touched the boundaries of traditional science, human cognition also faces a similar uncertainty principle: the uncertainty of fuzziness and randomness - two fundamentally different kinds of uncertainty. To date, no one has clearly explained the fundamental differences between these uncertainties and their origins. Although various machine learning methods can extract hidden information from data to some extent, the impact of cross-scale uncertainty always exists, representing an unavoidable long-term challenge for artificial intelligence applications.

Biosketch

Han-Xiong LI received his B.E. degree in aerospace engineering from the National University of Defence Technology, China, M.E. degree in electrical engineering from Delft University of Technology, Delft, The Netherlands, and Ph.D. degree in electrical engineering from the University of Auckland, Auckland, New Zealand. Currently, he is a chair professor in the Department of Systems Engineering, the City University of Hong Kong. Over the past thirty years, he has had the opportunity to work in different fields, including industry and academia. He published about 300 SCI journal papers with h-index 62 (web of science). Since 2014, he has been continuously rated as highly cited scholar in China by Elsevier. Since 2021, he has been continuously ranked among top 2% most cited scientists in the world by the Stanford University. His current research interests are in area of intelligent manufacturing, including process modeling and control, intelligent learning, distributed parameter systems, battery management system, etc. He was awarded the Distinguished Young Scholar (overseas) by the China National Science Foundation in 2004, a Chang Jiang scholar by the Ministry of Education, China in 2006, and a scholar in China Thousand Talents Program in 2010. He is a fellow of the IEEE.