Keynote Speakers

Prof. Marcelo H Ang Jr

National University of Singapore (NUS), Singapore

Biography: Marcelo H. Ang, Jr. received his BSc and MSc degrees in Mechanical Engineering from the De La Salle University in the Philippines and University of Hawaii, USA in 1981 and 1985, respectively, and his PhD in Electrical Engineering from the University of Rochester, New York in 1988 where he was an Assistant Professor of Electrical Engineering. In 1989, he joined the Department of Mechanical Engineering of the National University of Singapore where he is currently a Professor and the Past (Founding) Director of its Advanced Robotics Center. His research interests span the areas of robotics, mechatronics, autonomous systems, and applications of intelligent systems. He teaches robotics and related areas. In addition to academic and research activities. He is also actively involved in the Singapore Robotic Games as its founding chairman, and the IEEE Robotics and Automation Society. Some videos of his research can be found in: http://137.132.146.218/marcelo/videos/.

Speech Title: Industrial Robots to Everyday Robotics

Abstract: Robotics science and technology have evolved far beyond their original industrial roots in manufacturing, and now shape a wide range of sectors, including services, healthcare, education, and entertainment. Today, robots are becoming an integral part of everyday life, operating in unstructured environments and emphasizing human-centered interaction. They increasingly work alongside us, enhancing both productivity and quality of life. This talk will highlight recent advances in the core robotic capabilities of mobility and manipulation, and examine the key challenges that must be addressed to drive the next wave of the robotics revolution.

Prof. David Banjerdpongchai

Chulalongkorn University, Thailand

Biography: David Banjerdpongchai has been with the department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University. Currently, he is a professor of Electrical Engineering and head of Center of Excellence in Intelligent Control Automation of Process Systems. He is a senior member of IEEE, a founding chair of IEEE Control Systems Society Thailand Chapter, Vice President of ECTI Association (2022-2023), President of ECTI Association (2024-2025), an executive board member of ECTI Association, and a chair of IEC TC65 Thailand National Committee. In the past, he served as a chair of Systems and Control Technical Committee of ECTI Association and a member of Steering Committee of Asian Control Association. He served as General Co-chair of ECTI-CON 2013, ICA-SYMP 2019, ECTI-CON 2024, ECTI-CON 2025, SICE FES 2025, and TPC chair of ECTI-CON 2014 and TPC Co-chair of SICE 2020. He has served as an Associate Editor for IJCAS and a Section Editor-in-Chief for ASEAN Engineering Journal. He has published over 200 articles in journal and conference proceedings and a textbook on Dynamical Control Systems. His research interests are energy management systems, advanced process control, iterative learning control, and robust control applications.

Speech Title: Design of Supervisory Model Predictive Control for HVAC Systems

Abstract: This talk presents recent trends in energy intensity and energy demand in ASEAN and addresses key energy policies as part of Thailand 4.0. Electricity consumption has been increasing significantly due to the earth’s rising global temperatures, leading to higher energy usage in Heat, Ventilation and Air Condition (HVAC) systems. Choosing the conventional setpoint temperature could reduce unnecessary power consumption, thus leading to cost savings. This talk presents the design of Supervisory Model Predictive Control (SMPC) for HVAC systems with multiple zones. The design aims to shave the peak demand and maintain occupants’ thermal comfort. Two methods of SMPC are developed, namely, centralized SMPC and decentralized SMPC.  We apply the sparse Quadratic Programming (QP) solver using the interior point method. The results indicate that centralized supervisory control yields better outcomes, as demonstrated by a trade-off curve between total operating costs and thermal comfort. Moreover, centralized model predictive control successfully achieved satisfactory results in both tracking the reference signal and optimizing power consumption. Utilizing the sparse QP solver can yield faster computation compared to the standard QP solver, making it more suitable for the design of SMPC.

Prof. Xingjian Jing

City University of Hong Kong, China

Biography: Xingjian Jing (M’13, SM’17) received the B.S. degree from Zhejiang University, China, the M.S. degree and PhD degree in Robotics from Shenyang Institute of Automation, Chinese Academy of Sciences, respectively. He also achieved the PhD degree in nonlinear systems and signal processing from University of Sheffield, U.K. He is now a Professor with the Department of Mechanical Engineering, City University of Hong Kong. Before joining in CityU, he was a Research Fellow with the Institute of Sound and Vibration Research, University of Southampton, followed by assistant professor and associate professor with Hong Kong Polytechnic University. His current research interests include: Nonlinear dynamics, Vibration, Control and Robotics, with a series of 280+ publications of 16500+ citations and H-index 67 (in Google Scholar), with a number of patents filed in China and US. He is one of the world top2% highly cited scientists and IEEE senior member. Prof Jing is the recipient of a number of academic and professional awards including 2016 IEEE SMC Andrew P. Sage Best Transactions Paper Award, 2017 TechConnect World Innovation Award in US, 2017 EASD Senior Research Prize in Europe and 2017 the First Prize of HK Construction Industry Council Innovation Award, etc. He currently serves (or served) Senior Editor of Mechanical Systems and Signal Processing, Topic Associate Editor of Nonlinear Dynamics, and Associate Editors of IEEE Transactions on Systems, Man, Cybernetics -Systems, IEEE Transactions on Industrial Electronics (2021-2024), and Technical Editor of IEEE/ASME Trans. on Mechatronics (2015-2020). He was lead editors of special issues on “Exploring nonlinear benefits in engineering” during 2018-2019 and “Next-generation vibration control exploiting nonlinearities” during 2021-2022 both published in Mechanical Systems and Signal Processing. He is the general conference chair of ICANDVC 2021-2025.

Speech Title: Harnessing Nonlinearity for Smarter Engineering Systems

Abstract: Nonlinear dynamics underpins most engineering practices and often presents the greatest challenge that must be addressed before meaningful progress can be made. Gaining a deep understanding of nonlinearity is essential, as it offers direct insight into how nonlinear behavior shapes the response of dynamic systems. With this motivation, our work began years ago with the development of fundamental theories for nonlinear analysis and design. Building on these theoretical foundations, we then explored real engineering applications, leveraging nonlinear dynamics to achieve advantageous system responses. This progression has ultimately driven innovations in vibration control, energy harvesting, sensor design, structural health monitoring, and robotic systems. This talk provides an overview of these research and development efforts over the past years.

Prof. Mingbo Zhao

Donghua University, China

Biography: Mingbo Zhao received the Ph.D. degree from City University of Hong Kong in February 2013. He joined the School of Information Science and Technology at Donghua University in 2026, where he was appointed as a Full Professor and Ph.D. Supervisor in the Automation program. He currently serves as an Associate Editor for several SCI-indexed journals, including IEEE Transactions on Consumer Electronics, IEEE Transactions on Consumer Electronics Letters, and IEEE Transactions on Industrial Informatics. He is also an Associate Editor of the SCI journal International Journal of Pattern Recognition and Artificial Intelligence and a Domain Editorial Board Member of the Chinese core journal Computer Engineering. He has served as a Senior Program Committee Member of the AAAI Conference on Artificial Intelligence (2022–2025) and as an Area Chair for ACM Multimedia (2021–2023), and has also served on the program committees of multiple international conferences and as a reviewer for numerous leading journals. His research interests include machine learning and artificial intelligence, with a focus on multimodal information retrieval, fault diagnosis, and medical diagnosis. Over the past five years, he has published more than 100 papers in leading international journals and conferences in artificial intelligence, authored two book chapters, obtained one U.S. invention patent and five Chinese invention patents, and led three research projects, including a General Program of the National Natural Science Foundation of China, while also participating as a key member in a National Major Science and Technology Project of China. His publications have received more than 4,000 citations on Google Scholar, indicating significant academic impact both nationally and internationally.

Speech Title: Embodied Mapless Navigation for Autonomous Robots

Abstract: Embodied mapless navigation has emerged as a key capability for autonomous robots operating in complex and dynamic real-world environments. Unlike traditional navigation methods that rely heavily on pre-built maps and precise localization, embodied mapless navigation enables robots to perceive, understand, and interact with their surroundings directly through multimodal sensory inputs and intelligent decision-making mechanisms. This report introduces the fundamental concepts and recent progress of embodied mapless navigation, focusing on how autonomous robots achieve perception, navigation, and action coordination in unknown environments. The potential of embodied intelligence for future robotic systems is also briefly discussed.

Prof. Genci Capi

Hosei University, Japan

Biography: Genci Capi received the Ph.D. degree from Yamagata University, in 2002. He was a Researcher at the Department of Computational Neurobiology, ATR Institute from 2002 to 2004. In 2004, he joined the Department of System Management, Fukuoka Institute of Technology, as an Assistant Professor, and in 2006, he was promoted to Associate Professor. He was a Professor in the Department of Electrical and Electronic Systems Engineering, at the University of Toyama up to March 2016. Now he is a Professor in the Department of Mechanical Engineering, Hosei University. His research interests include intelligent robots, BMI, multi-robot systems, humanoid robots, learning and evolution.

Prof. Josué Antonio Nescolarde Selva

University of Alicante. Alicante, Spain

Biography: Josué Antonio Nescolarde Selva obtained his Mathematics degree from the University of Havana (Cuba) in 1999, receiving the Gold Medal in Mathematics in that same year. He later completed his PhD in Applied Mathematics at the University of Alicante (Spain) in 2010. Since 2002, he has been a member of the Department of Applied Mathematics and Aerospace Engineering at the University of Alicante. Since last year, he has also served as Dean of the Polytechnic School. He has authored or coauthored over 100 journal articles and books. He stands out for his international research collaboration with scholars from various parts of the world, including Ireland, the United States, China, among others. His research interests include Cybernetics, Data Science, Philosophy of Science, General Systems Theory, and the modeling of complex social systems.

Speech Title: Complexity, Networks and Prediction

Abstract: Complex Systems is an emerging scientific field that examines how the interactions among individual components of a system lead to its overall behavior, as well as how the system relates to its surrounding environment. In these systems, causal relationships are typically circular rather than linear, meaning that outcomes are not driven by a single cause but instead arise from the interplay of both positive and negative feedback processes. Moreover, the study of complex systems has significantly improved our understanding across a wide range of important domains, including biology, economics, social sciences, and technology. One of the key advantages of adopting a network perspective is the availability of a vast set of mathematical tools for analyzing different types of network models and uncovering hidden patterns. Interpreting complex systems through networks also enables the application of concepts such as coverage and invariance, along with other related ideas, providing deeper insights into structure, dynamics, and long-term system behavior. In the field of robotics, these principles are particularly relevant, as robotic systems often consist of multiple interacting components such as sensors, actuators, and control algorithms. Understanding robots as complex systems allows researchers to design more adaptive, resilient, and autonomous machines, especially in areas like swarm robotics, human-robot interaction, and distributed control, where collective behavior emerges from local interactions.

Prof. Chieko Kato

Toyo University, Japan

Biography: Chieko Kato is Dean and Professor of the Faculty of Information Sciences, Toyo University. She completed her Master's degree at the Graduate School of Education, University of Tokyo (Educational Psychology Course), and received her Ph.D. in Engineering from Hosei University in 2007. She previously served as a lecturer at Oita Prefectural College of Arts and Culture before joining Toyo University, where she progressed from lecturer to associate professor, professor, and department chair, assuming the position of Dean in April 2021. She holds qualifications as a certified public psychologist, clinical psychologist, art therapist, yoga therapist, and certified social researcher. She has published over 70 peer-reviewed papers, 28 books and book chapters, and 110 oral and invited presentations, spanning clinical psychology, sport psychology, art therapy, yoga therapy, and psychometrics. Her research focuses on the intersection of psychology and information science, with applications in mental health care for students and adults, mental training for athletes, and AI-assisted psychological assessment. She also practices counseling at a psychiatric clinic, providing multifaceted support incorporating art therapy and yoga therapy.

Speech Title: The Roles and Growing Applications of AI and Robotics in Care and Therapy

Abstract: Mental health care and therapeutic support face growing demand across diverse populations, including students, working adults, older adults, and athletes, yet access to professional psychological services remains limited. Recent studies have demonstrated that AI-assisted CBT support can reduce treatment dropout rates and improve recovery outcomes (Habicht et al., 2025), and that social robots can alleviate loneliness and enhance psychological well-being among older adults (Murayama & Takase, 2025). These findings reflect the rapid advancement of AI and robotics in clinical psychology. Building on these developments and drawing on the presenter's own research, this presentation introduces a range of exploratory applications in clinical psychology, including AI-assisted approaches for analyzing projective tests such as the Baum Test and sandplay therapy, yoga therapy outcome measurement, and robotics-based social and emotional support, among others. Preliminary findings from studies involving various populations, including university students, athletes, and older adults, will be presented, illustrating how technology can enhance, not replace, the human dimensions of care. This presentation highlights both the promise and the challenges of integrating AI and robotics into therapeutic practice, pointing toward a future in which compassionate, data-informed psychological support becomes more widely accessible.

Prof. Leijie Lai

Shanghai University of Engineering Science, China

Biography: Dr. Leijie Lai, Associate Professor of Mechanical and Automotive Engineering School, Shanghai University of Engineering Science. He has been supported by the Shanghai Talent Development Fund and has presided over two projects of the National Natural Science Foundation of China and one project of the Shanghai Natural Science Foundation. He has long been engaged in the research on nano-precision displacement drive and control, and compliant mechanisms, publishing over 30 papers.

Speech Title: Electromagnetic Driven Multi-DOF Precision Motion Platform: Design, Modeling and Control

Abstract: This speech presents the design, modeling, and control of two types of electromagnetic driven precision positioning platforms. The first is a six-degree-of-freedom compliant micropositioning stage driven by voice coil motors, featuring eight parallel driving branch chains with parallelogram flexure mechanisms and large-stroke flexible ball joints for decoupling. The second is a three-degree-of-freedom tip-tilt-piston stage driven by reluctance actuators arranged at 120° intervals, where a rational polynomial combined with a Prandtl-Ishlinskii inverse hysteresis model is developed to compensate for nonlinearities and improve tracking accuracy. This work provides a comprehensive framework for the design and control of high-performance multi-DOF electromagnetic driven precision positioning systems.