Keynote Speaker I
Prof. Jean-luc Dugelay
EURECOM
IEEE Fellow
Biography: Jean-Luc DUGELAY obtained his PhD in Information Technology from the University of Rennes in 1992. His thesis work was undertaken at CCETT (France Télécom Research) at Rennes between 1989 and 1992. He then joined EURECOM in Sophia Antipolis where he is now a Professor in the Department of Digital Security. His current work focuses in the domain of multimedia image processing, in particular activities in security (image forensics, biometrics and video surveillance, mini drones), and facial image processing. He has authored or co-authored over 285 publications in journals and conference proceedings, 1 book on 3D object processing published by Wiley, 5 book chapters and 3 international patents. His research group is involved in several national projects and European projects. He has delivered several tutorials on digital watermarking, biometrics and compression at major international conferences such as ACM Multimedia and IEEE ICASSP. He participated in numerous scientific events as member of scientific technical committees, invited speakers or session chair. He is a fellow member of IEEE, IAPR, and AAIA; and an elected member of the EURASIP BoG. Jean-Luc Dugelay is (or was) associate editor of several international journals (IEEE Trans. on IP, IEEE Trans. on MM) and is the founding Editor-in-Chief of the EURASIP journal on Image and Video Processing (SpringerOpen). Jean-Luc DUGELAY is co-author of several conference articles that received an IEEE award in 2011, 2012, 2013 and 2016. He co-organized the 4th IEEE International Conference on Multimedia Signal Processing held in Cannes, 2001 and the Multimodal User Authentication held in Santa Barbara, 2003. In 2015, he served as general co-chair of IEEE ICIP (Québec City) and EURASIP EUSIPCO (Nice).
Keynote Speaker Ⅱ
Prof. Yun Li
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China
IEEE Fellow
Biography: Professor Yun Li FIEEE obtained his PhD from University of Strathclyde, Glasgow, UK, and has researched into intelligent systems and "AI for Engineering" for over 30 years. He taught at University of Glasgow for 28 years, where he was recognized as the second Top Author and served as the founding Director of University of Glasgow Singapore. Since 2021, he has been Director of Industrial Artificial Intelligence Centre at Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China.
Inspired by AI, his early work resolved issues in PID control that had been puzzling practicing engineers for over 50 years. He has led or co-led over 30 research projects in the UK, EU, Singapore, and China, equivalent to over 20 million pounds in funding. Currently, his research focuses on explainable artificial intelligence (XAI) and Computer-Automated Design (CAutoD, EDA), leading 2 major research projects funded by the National Natural Science Foundation of China for the next-generation AI models with grey-box XAI technology and by the National Key R&D Program of the Ministry of Science and Technology of China for the next-generation AI chips with compute-in-memory technology. He has published over 300 papers and books, and holds 20 patents in China, Europe, United States and Japan.
Speech Title: Knowledge and Data Dual-Driven Artificial Intelligence to Enable Computer-Automated Design
Abstract: The explosive growth in data volume and computational power has enabled the successful application of computational artificial intelligence (AI) in engineering science ("AI for Engineering"), greatly enhancing industrial innovation in terms of exploration, imagination, and creativity. This lecture introduces, in conjunction with general large language models (LLM), the next generation of artificial intelligence that is explainable (XAI), driven by both data and knowledge. It illustrates the elevation of "Computer-Aided Design" (CAD) in the third paradigm of science to "Computer-Automated Design" (CAutoD) in the fourth paradigm. Similar to how AlphaGo Zero, which was not based on human intelligence, surpassed AlphaGo, which was based on Go experts, this approach aims to break through the mental limits of design engineers, enhance the performance of high-end products and services, shorten development time, and increase industrial competitiveness and originality. In addition to engineering design and electronic design automation (EDA), the talk will also cover applications of XAI in dynamic system modelling, control signal generation, and track-before-detection filtering for unmanned systems.
Invited Speaker I
Dr. Qiang Zhang
North University of China
Biography: Zhang Qiang received the M.S. degree in operations science and control theory from the school of science, Northeastern University, Shenyang, China, in 2019, and the Ph.D. degree in control science and engineering from the school of information science and engineering, Northeastern University, in 2023. Currently, as a lecturer at North University of China. His research interests include advanced aircraft guidance and control, intelligent control theory and methods, adaptive control, switched control, and cyber-physical systems.
Speech Title: Adaptive Fuzzy Non-Fragile Prescribed Performance Fine Anti-Disturbance Control Method for Variable Sweep Wing Aircraft
Abstract: By changing the sweep angle of the wing, the variable sweep wing aircraft has obvious advantages in coordinating supersonic flight, subsonic cruise and short moment take-off and landing. This change brings challenges to the modeling, disturbance rejection control and performance optimization of variable sweep wing aircraft, such as the difficulty of variant structure characterization, multi-source disturbance estimation and control performance optimization. Aiming at the above problems, this project is based on the idea of innovative modeling, fine anti-disturbance and autonomous intelligence, and covers the following three aspects. First of all, a continuous model based on quantization switching mechanism is built to remedy the defect of discrete modeling caused by non-quantization and discontinuity of switching mechanism. Secondly, in order to mitigate the adverse effects of multi-source disturbances, a design framework based on ＂feedforward+feedback＂ disturbance observer is proposed to implement fine anti-disturbance for variable sweep wing aircraft. Finally, to ensure transient and steady-state performance during flight, a non-fragile prescribed performance control intelligent strategy is constructed that includes autonomous perception, envelope adjustment, and prescribed reachability. Improving the controller singularity phenomenon that is prone to occur in traditional prescribed performance control theory. The research of this project is expected to provide guarantee for our variable sweep wing aircraft to run more accurately, reliably and efficiently, and to meet the needs of national technology development and equipment development.