Youmin Zhang (IEEE Fellow, CSME Fellow)
Concordia University, Canada
BIO: Dr. Youmin Zhang is currently a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University, Canada. His research interests include monitoring, diagnosis, and physical fault/cyber-attack tolerant /resilient control of unmanned systems and smart grids. These research areas have applications in forest fire management and smart cities within the framework of cyber-physical systems, combining remote sensing and image processing techniques. He has published 10 books and over 700 journal and conference papers, which have been cited up to 34,230 times on Google Scholar with an h-index of 90 and i10-index of 457 currently. His publications have been ranked in Lifetime as #1 Globally in the Specialties of both "Aircraft Systems" and "Fault Tolerance", and #2 Globally in the Specialty of "Unmanned Aerial Vehicle" according to the recent rankings by ScholarGPS. He has also been consistently listed in the Stanford’s “World’s Top 2% Scientists” since its first list in 2021 and selected as a 2025 Highly Cited Researcher by Clarivate. Prof. Zhang is a Fellow of IEEE and CSME and served as the President of the International Society of Intelligent Unmanned Systems from 2019 to 2022. He is currently serving as the International Director (Region 7) of the IEEE Aerospace and Electronic Systems Society (AESS). Additionally, he has held roles as (Associate/Deputy) Editor-in-Chief, and (Advisory) Editorial Board Member and Associate Editor for more than 20 journals. Additionally, he has served as (Honorary) General Chair and Program Chair for several conferences related to autonomous/unmanned systems, renewable energies, and smart cities many times. More detailed information can be found at: http://users.encs.concordia.ca/~ymzhang/.
Speech Title: Safety and Security (S&S) Challenges and New Developments in Autonomous Unmanned Systems towards Low-Altitude Economy Applications
Abstract: Although the concepts and developments on Fault Detection and Diagnosis (FDD) and Fault-Tolerant Control (FTC) have been extensively investigated worldwide since the 1970s and 1980s, respectively, the catastrophic crashes of two Boeing 737 MAX8 airplanes in 2019 have again highlighted the necessity and urgency for FDD and FTC research & development and their industrial applications. On the other hand, the low-altitude economy is developing rapidly in China and other countries around the world. What are the key challenges and technologies for safe and secure autonomous/uncrewed flight in these low-altitude economy environments? In this speech, brief overall view on the challenges and latest developments towards smarter, safer, more reliable and more resilient autonomous/uncrewed/unmanned systems in terms of safe and secure controls of these systems with integration of Remote Sensing (RS) techniques for low-altitude economy applications such as forest fires detection and fighting will be presented first, then some of new developments and current research works being carried out at our group will be introduced secondly. In particular, new developments on FDD, FTC, and Fault/Attack-Tolerant Cooperative Control (FTCC) techniques towards autonomous, safe and secure operations of unmanned systems for forest fire and smart cities monitoring and detection tasks in the presence of physical-faults/damages and cyber-attacks will be presented.
Angelo Cangelosi
University of Manchester, UK
BIO: Angelo Cangelosi is Professor of Machine Learning and Robotics at the University of Manchester (UK) and co-director and founder of the Manchester Centre for Robotics and AI. He was selected for the award of the European Research Council (ERC) Advanced grant (funded by UKRI). His research interests are in cognitive and developmental robotics, neural networks, language grounding, human robot-interaction and trust, and robot companions for health and social care. Overall, he has secured over £40m of research grants as coordinator/PI, including the ERC Advanced eTALK, the UKRI TAS Trust Node and CRADLE Prosperity, the US AFRL project THRIVE++, and numerous Horizon and MSCAs grants. Cangelosi has produced more than 400 scientific publications. He is Editor-in-Chief of the journals Interaction Studies and IET Cognitive Computation and Systems, and in 2015 was Editor-in-Chief of IEEE Transactions on Autonomous Development. He has chaired numerous international conferences, including ICANN2022 Bristol, and ICDL2021 Beijing. His book “Developmental Robotics: From Babies to Robots” (MIT Press) was published in January 2015, and translated in Chinese and Japanese. His latest book “Cognitive Robotics” (MIT Press), coedited with Minoru Asada, was recently published in 2022 (Chinese translation in 2025).
Speech Title: The Importance of Starting Small with Baby Robots: Developmental Robotics for Language Grounding
Abstract: Cognitive developmental robotics aims to develop robots capable of human-like learning, interaction, and behavior by grounding concrete and abstract concepts in sensorimotor experiences and social interactions. This talk introduced examples on language grounding in cognitive developmental robotics, and explores how principles like “starting small”, “embodied intelligence” and “super-embodiment” can address the limitations of AI tools, such as large language models (LLMs), which rely heavily on large datasets and lack sensorimotor grounding. By integrating incremental, multimodal learning and redefining embodiment to encompass physical, mental, and social processes, we can enable robots to better understand and utilize abstract concepts. The talk will also reflect on the pros and cons of using foundation models in cognitive robotics.
Ching-Chih Tsai (IEEE Fellow)
National Chung Hsing University, Taiwan
BIO: Ching-Chih Tsai received the Diploma degree in electrical engineering from the National Taipei Institute of Technology, Taipei, Taiwan, in 1981, the M.S. degree in control engineering from National Chiao Tung University, Hsinchu, Taiwan, in 1986, and the Ph.D. degree in electrical engineering from Northwestern University, Evanston, IL, USA, in 1991. He is currently a Life Distinguished Professor at the Department of Electrical Engineering, National Chung Hsing University (NCHU), Taichung. He has been elevated as the Fellow of Institute of Electrical and Electronic Engineering (IEEE), Institute of Engineering Technology (IET), Chinese Automatic Control Society (CACS), Robotics Society of Taiwan (RST), and Taiwan Fuzzy Systems Association (TFSA). From 2003 to 2005, he served as the Director of the Center of Research Development and Engineering Technology, College of Engineering, National Chung Hsing University. In 2006, he served as the Director of the Center for Advanced Industry Technology and Precision, National Chung Hsing University. He served as the department chair of the Department of Electrical Engineering, NCHU, from 2012 to 2014. From 2012 to 2016, he served two-term President of the Chinese Automatic Control Society (CACS), Taiwan. From 2016 to 2019, he served two-term President of the Robotics Society of Taiwan (RST). From 2019 to 2023, he served as the President Elect and President for International Fuzzy Systems Association (IFSA), respectively. Since August, 2024, he has served as the Dean of College of Electrical Engineering and Computer Science. He also served as two-term BoG members of IEEE SMCS from 2017 to 2019 and from 2022 to 2024, respectively. In recent years, he has served associate editors of IEEE Transactions on Systems, Man Cybernetics: Systems, IEEE Transactions on Industrial CPS, and International Journal of Fuzzy Systems, respectively. He has published and co-authored more than 700 technical articles. His current research interests include intelligent control systems, smart mobile robotics and intelligent automation with their applications to smart hospitals, semiconductor manufacturing and clean energy.
Speech Title: Technology Development and Field Verifications of AI-Based Nursing Robots in a Smart Hospital
Abstract: To overcome the six technical pain points caused by medical nursing and material handling robots currently faced by smart hospitals, this talk is aimed to design and implemented smart nursing robots some breakthrough techniques by integrating discriminative AI technologies (including deep learning, broad learning, reinforcement learning), generative AI (GAI), intelligent control, embedded control, autonomous mobile robots (AMR) and AI chip design technologies. These new smart nursing robots have generative-AI robot control frameworks and multi-modal natural human-computer interaction, and even have some breakthrough techniques and methodologies such as more advanced V-SLAM chip designs with hardware accelerators, GAI autonomous navigation and task generation and execution, reliable smart conversation or dialogue, AI visual environment perception, intelligent multi-robot assignment and scheduling, digital twin with robot task planning, in order to achieve medical nursing and equipment handling tasks in the cluttered, dynamic and crowded smart hospital space. This talk will focus on how to deeply develop these breakthrough technologies for medical nursing robots and how to proceed with the robots’ field verifications in the Chang Chi Hospital, Changhua, Taiwan, in order to better address the practical issues of smart hospitals. Some experimental results will be companied with the proposed methods together with the built robot.
David Banjerdpongchai
Chulalongkorn University, Thailand
BIO: David Banjerdpongchai received B.Eng. degree (First class honors) from Chulalongkorn University, and M.S. and Ph.D. degrees from Stanford University, all in Electrical Engineering, respectively. He has been with the department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University. Currently, he is a professor of Electrical Engineering and the head of the Center of Excellence in Intelligent Control Automation of Process Systems. He is a senior member of IEEE, President of ECTI Association (2024-2025), and a founding chair of IEEE Control Systems Society Thailand Chapter (2015-2021). He served as a general co-chair of ECTI-CON 2013, ICA-SYMP 2019, ECTI-CON 2024, ISCIT 2024, ECTI-CON 2025, SICE FES 2025, associate editor of IJCAS and a section editor-in-chief of ASEAN Engineering Journal. His research interests are energy management systems, control design of nonlinear systems, and convex optimization in robust control problems.
Speech Title: Robust Iterative Learning Control for Flexible Link System
Abstract: This research proposes a convex optimization design of robust iterative learning control (ILC) algorithm for linear systems subject to parametric uncertainties. The system model is described by the Markov matrix as an affine function of parametric uncertainties. The robust ILC design is formulated as a min-max problem using a quadratic performance criterion subject to constraints of the control input update. We reformulate the design problem as a convex optimization over linear matrix inequalities (LMIs). The LMI-based design problem can efficiently solved using available convex optimization software. The robust ILC algorithm has been developed, and the convergence of the control input and the error can be guaranteed. We conduct a computer simulation of the robust ILC algorithm with a flexible link model and verify with the implementation on a real flexible link system. The objective of control for the flexible link is to iteratively track the desired reference angle under the parameter variation such as the change of load mass. The experiment results are close to the simulation results. Thus, the robust ILC algorithm can be effectively applied to the flexible link system.
Guoqiang Hu
Nanyang Technological University, Singapore
BIO: Guoqiang Hu is a Professor of Intelligent Systems and Robotics in the School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore. He received Ph.D. in Nonlinear Control and Robotics from University of Florida. His research interests include optimization and control, game theory, and AI algorithms, with applications to human-robot collaboration, collaborative robots, and multi-robot systems. He serves/served as Associate Editor for IEEE Transactions on Automatic Control (2019-2025) and Automatica (2025-2028), Technical Editor for IEEE/ASME Transactions on Mechatronics (2017–2020), and Associate Editor for IEEE Transactions on Automation Science and Engineering (2017–2020). He also served as Program Chair/Co-Chair for IEEE ICCA 2016, IEEE IECON 2020 and IEEE CDC 2023, and General Chair for ICARCV 2018 and IEEE ICCA 2020. He has published 1 book and 300+ referred papers in journals and conferences, with Google Scholar Citations 15000+ and H-Index 68. He was a recipient of several awards, including the Best Paper in Automation Award in the 14th IEEE International Conference on Information and Automation, the Best Paper Award in the 36th Chinese Control Conference, and the Best Paper Award in the 4th Asia Pacific Conference of the Prognostics and Health Management Society. He is a Clarivate Highly Cited Researcher (2025).
Speech Title: Safe Human-Robot Collaboration
Abstract: Human–robot collaboration (HRC) has emerged as a cornerstone for the next generation of intelligent manufacturing, service robotics, and human-centric automation. Unlike traditional industrial robots confined to isolated tasks, collaborative robots must share workspace, goals, and decision-making processes with humans, requiring real-time safety, adaptability, and efficiency. One of the challenges for multi-robot systems and human-robot systems is the design of effective algorithms that enable the robots to work cooperatively and safely with other robots or humans. Optimization provides a unifying mathematical framework to formalize these challenges. This talk will first give a brief review on human-robot collaboration, and then present some recent related research results.