Keynote Speakers

Prof. Marcelo Ang

National University of Singapore (NUS), Singapore

Biography: Marcelo H. Ang Jr. received the B.Sc. degrees (Cum Laude) in mechanical engineering and industrial management engineering from the De La Salle University, Manila, Philippines, in 1981, the M.Sc. degree in mechanical engineering from the University of Hawaii at Manoa, Honolulu, HI, USA, in 1985, and the M.Sc. and Ph.D. degrees in electrical engineering from the University of Rochester, Rochester, NY, USA, in 1986 and 1988, respectively.,His work experience includes engineering work in Intel, research positions at the East West Center, Honolulu, and at Massachusetts Institute of Technology, Cambridge, MA, USA, and an Assistant Professor of electrical engineering at the University of Rochester. In 1989, he joined the Department of Mechanical Engineering, National University of Singapore, Singapore, where he is currently a Professor. His research interests span the areas of robotics, mechatronics, autonomous vehicles, and applications of intelligent systems methodologies. His teaching includes graduate and undergraduate level courses in robotics. He is also active in consulting work in robotics and intelligent systems.,Dr. Ang is actively involved in Singapore Robotic Games as the Founding Chairman and the World Robot Olympiad as a member of its Advisory Council.

Prof. David Banjerdpongchai

Chulalongkorn University, Thailand

Biography: 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.

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.

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.