Prof. Zheng Hong (George) Zhu

York University,  Canada

Bio.: Dr. Zheng Hong (George) Zhu is a leading authority in space robotics and computational control, serving as Professor & Tier 1 York Research Chair in Space Robotics and Artificial Intelligence in the Department of Mechanical Engineering at York University in Canada. He received his Bachelor, Master and PhD degrees from Shanghai Jiao Tong University, Master of Applied Science from University of Waterloo and PhD from University of Toronto. 

His research spans spacecraft dynamics and control, tethered space systems, autonomous space robotics, computational control methodologies, and in-space additive manufacturing. He has published over 239 peer-reviewed journal papers and 186 conference papers, establishing an international reputation in astronautics and mechatronics. 

Dr. Zhu is an academician of the International Academy of Astronautics; a College Member of the Royal Society of Canada; a Fellow of the Canadian Academy of Canada, the Engineering Institute of Canada, the Canadian Society of Mechanical Engineering (CSME), and the American Society of Mechanical Engineers (ASME). He is also the Associate fellow of the American Institute of Aeronautics and Astronautics (AIAA). His achievements have been recognized with numerous prestigious awards, including the 2024 Solid Mechanics Medal and 2021 Robert W. Angus Medal (CSME), the 2024 Gold Medal and 2019 Engineering R&D Medal of Ontario Professional Engineers Awards, and the 2021 York University President’s Research Excellence Award.

Title: Towards a Unified Computational Framework for Modeling and Control

How can we design feedback laws for complex systems with the same universality that the Finite Element Method (FEM) brought to engineering analysis? This keynote introduces a universal computational framework that unifies modeling, stability, and optimal control of flexible and distributed-parameter systems. From spacecraft with large deployables to next-generation mechatronic platforms, discover how this approach makes advanced nonlinear control as systematic and scalable as FEM itself. Accurate control of spacecraft with flexible structures—such as tethers, solar panels, and booms—remains a critical challenge. Traditionally, this requires deep expertise and case-specific design, and no general methodology exists to algorithmically synthesize feedback laws for coupled rigid–flexible dynamics or infinite-dimensional systems. Our approach bridges this gap by extending the FEM paradigm to control: stable feedback laws are synthesized at the element level using Lyapunov theory, Pontryagin’s maximum principle, Hamiltonian mechanics, and computational solid mechanics, then assembled into a global law with rigorous guarantees of stability and controllability. By embedding these methods into existing FEM programs, advanced nonlinear control becomes as systematic, scalable and automatable for engineers as FEM is today. Numerical studies demonstrate the effectiveness of this methodology for spacecraft and next-generation mechatronic applications.

Prof. Yoong Choon Chang

Universiti Tunku Abdul Rahman (UTAR), Malaysia

Bio.: Ir. Prof. Dr. CHANG Yoong Choon is a Professor and Head of the Department of Electrical & Electronic Engineering at Universiti Tunku Abdul Rahman (UTAR). He is also the Director of XDU-UTAR Institute of Science, Technology and Innovation, jointly setup by Xidian University China and UTAR. He earned his BEng (First Class Honours) from the University of Northumbria at Newcastle, UK, and both his Master of Engineering Science and PhD (Engineering) from Multimedia University, Malaysia.

Prof. Chang’s extensive research interests keenly align with the evolving landscape of intelligent transportation. His work particularly focuses on the practical applications of artificial intelligence, wireless communications, and signal processing in areas such as smart homes, ambient assisted living, and vehicular communication. He has been a driving force in numerous research projects, including those on digital home technologies and cognitive radio-enabled vehicular cyber-physical systems.

Title: Enhancing Mechatronics Research Productivity using AI Tools

The multidisciplinary nature of mechatronics, integrating mechanical, electronic, and software engineering, presents unique and complex research challenges. In an era demanding rapid innovation, the traditional research lifecycle can be a significant bottleneck. This keynote explores the transformative role of modern Artificial Intelligence (AI) tools in accelerating research productivity within the mechatronics domain. We will demonstrate how researchers can strategically leverage Large Language Models (LLMs) and specialized AI platforms—such as ChatGPT, Gemini, DeepSeek, and NotebookLM—to streamline and enhance every stage of their work.

Key applications to be discussed include expediting comprehensive literature reviews, generating and debugging complex code for simulations and control systems, analyzing experimental data, and refining manuscript drafts. By integrating these AI tools as intelligent research assistants, scholars can significantly reduce time spent on laborious tasks, allowing for a greater focus on novel problem-solving and conceptual innovation. This presentation will provide practical strategies and real-world examples, equipping attendees with the knowledge to harness AI as a powerful collaborator, thereby fostering a more dynamic, efficient, and productive research environment in mechatronics.

Prof. Xiaoping Zhang

Macau University of Science and Technology, China

Bio.: Zhang Xiaoping is a professor at Macau University of Science and Technology, deputy director of Space Science Institute and the State Key Laboratory of Lunar and Planetary Sciences. He completed both his undergraduate and doctoral studies at the School of Physics, Nanjing University. Zhang has conducted research at Lawrence Berkeley National Laboratory and Tsinghua University, among other institutions. 

 His primary research interests are lunar and planetary dust and radiation environments, as well as planetary remote sensing data analysis. Zhang has been involved in the development or data analysis and research for scientific payloads on China’s Chang'e 2–6 lunar missions, Tianwen-1 and Tianwen-2 missions, Macau Science Satellite 1, and the U.S. LADEE mission. He has published over 300 SCI-indexed papers, with more than 13,000 citations in SCI journals. Zhang received the Macau SAR Natural Science Award first prize in 2016 and second prize in 2022.

Title: Fundamental Characteristics of Lunar Regolith for Sustainable Resource Utilization

The utilization of lunar resources is essential for humanity's deep space exploration and long-term extraterrestrial presence, with lunar regolith representing the most accessible surface material and primary target for in-situ resource utilization (ISRU). This presentation addresses cutting-edge scientific challenges in lunar regolith characterization by integrating recent findings from Chang'E missions and terrestrial analogs, focusing on: electrostatic migration properties under low-gravity and high-vacuum conditions; mechanical behavior including cohesion, compaction, and shear strength for construction applications; stratigraphic distribution, dielectric properties and depth-dependent resource concentration; chemical composition variations across lunar terrains; and space weathering effects from solar wind, micrometeorite impacts, and cosmic radiation. These studies provide foundational knowledge for developing autonomous mechatronic systems to enable sustainable lunar operations and resource utilization.

Prof. Shijie Guo

Hebei University of Technology, China
Fudan University, China

Bio.: Prof. Shijie Guo received his doctor degree in mechanical engineering from Tokyo Institute of Technology, Japan, in 1992. He is currently a professor at Hebei University of Technology and a professor at Fudan University, China. He is also the director of the Hebei Key Laboratory of Robot Perception and Human-Robot Interaction as well as the Engineering Research Center of the Ministry of Education of China for Intelligent Rehabilitation Equipment and Physiological Information Detection. He also serves as the deputy director of the Academic Committee of Hebei University of Technology and editor-in-chief of Journal of Hebei University of Technology. He has long been engaged in the research of key technologies and applications of human-interaction robots, including robotic e-skin, electroactive polymer artificial muscles, nursing-care robots, rehabilitation robots, exoskeleton robots, etc. He has published over 200 papers in related fields. The intelligent robot skin tactile sensing system developed by his team was selected as the "Innovation China" pioneer technology by China Association for Science and Technology in 2020. The piggyback transfer robot he developed won the Gold Medal at the 8th China Entrepreneurial Design & Innovation Competition of Elderly Welfare Equipment in 2021. He won the first prize for scientific and technological progress in Hebei Province twice in 2022 and 2024. He holds over 40 invention patents.

Title: AI-powered Nursing-care Aids --- from Unifunctional Equipments to Multifunctional Humanoid Robots

With the acceleration of population aging, the expectations for practical applications of robots in nursing site are rapidly increasing. The research and development of nursing-care robots has become a hot topic in the field of robotics. At present, most nursing-care robots are unifunctional products which are designed only to accomplish a specific task, such as patient transfer, mobility, meal assistance, bathing, toilet treatment and so on. They can help to reduce the physical labor intensity of caregivers, and partially addressing the problem of insufficient caregivers by introducing AI technologies. However, although the unifunctional robots have their irreplaceable role, they cannot fundamentally solve the problem of insufficient caregivers as aging leads to multiple declines in physical and cognitive functions. Therefore, we need to develop multifunctional robots that can perform the tasks of “human operation”, “object operation” and “tool operation”. Here, “human operation” refers to body-contact tasks such as turning over the care receiver who is lying on a bed, cleaning the body, transfer assist, etc., “object operation” refers to the tasks of grasping and delivering objects, and “tool operation” refers to tool-using tasks such as feeding water/food/drag by using a spoon, pushing a wheelchair, etc. 

 There are two main lines in the research and development of nursing-care robots, one is unifuntional robots, the other is multifunctional ones. This talk will review the state of the art of unifunctional nursing-care robots, and then discuss the core technologies involved in humanoid nursing-care robots. It will focus on the applications of AI, including the challenges and applications of achieving autonomy for unifunctional robots, and the embodied intelligent humanoid robots. In the case of humanoid nursing-care robots, it will mainly discuss the learning of operational skills. When people perform fine operations, they generate actions based on vision and adjust the actions based on the feeling of touch. The relative motion and contact force between the human hand and the objects are the two physical items of operation, the two items are interrelated and intertwined, forming operational skills. How to make a robot to acquire the same operational skills as humans is a key issue. The method of learning from human demonstrations usually only learns the motor skills, but cannot well learn human perception and decision-making ability. The talk will present the attempts in our lab for solving the problem of skill learning.

Prof. Anees Ahmad Ansari

King Saud University, Saudi Arabia

Bio.: Dr. Anees Ahmad Ansari is a Full Professor at the King Abdullah Institute for Nanotechnology (KAIN), King Saud University, Riyadh, Kingdom of Saudi Arabia. He is a leading researcher in the field of luminescent nanomaterials, particularly focusing on trivalent lanthanide (Ln³⁺) ions and their applications in bioimaging, diagnostics, photovoltaics, and chemical sensing. Dr. Ansari has made significant contributions to the design, synthesis, and functionalization of rare-earth-doped nanostructures and metal oxide-based electrochemical biosensors. He received his Ph.D. in Chemistry from Jamia Millia Islamia University, New Delhi in 2004, followed by postdoctoral research at the University of Delhi and the National Physical Laboratory (CSIR-NPL). Dr. Ansari has authored over 220 peer-reviewed journal publications, contributed to 4 book chapters, and published 1 scientific book. As of April 2025, his work has garnered 9,300+ citations, with an h-index of 56 (Google Scholar). He has been named in the Stanford University Global Ranking of Top 2% Scientists for six consecutive years (2019–2024). His research emphasizes the development of cost-effective, eco-friendly synthetic routes, luminescence enhancement strategies, and device-level integration of advanced materials. Notably, his group has developed several lanthanide-doped oxide systems and rare-earth nanophosphors with improved quantum efficiency for photonic and biosensing platforms. Dr. Ansari is also a dedicated science communicator and mentor. He has delivered over 20 invited talks and keynote addresses, conducted international workshops, and supervised multiple graduate students and postdocs. His continued efforts to bridge fundamental research and applied nanotechnology position him among the most impactful researchers in the field of materials chemistry and nanoscience.

Title: Nanostructured Materials Powering the Future of Smart Sensing/Detection Technologies

This presentation delves into recent developments in the fabrication of high-resolution, multifunctional nanostructured-based sensor arrays enabled by MEMS/NEMS architectures, 3D nano-printing, and atomic layer deposition. The emphasis will be placed on label-free biosensing using plasmonic, and photonic crystal-based platforms, electrochemical transduction with nanostructured electrodes, and hybrid integration of 2D materials (e.g., carbonaceous, MoS₂, etc.) to enhance signal sensitivity and selectivity. The integration of advanced sensing detection technologies with micro- and nano-manufacturing platforms is catalyzing transformative innovations across biomedical diagnostics, environmental surveillance, and industrial automation. Current emerging approaches such as nanostructures deposited electrodes, flexible/stretchable substrates, and AI-integrated sensor fusion systems will be discussed, with case studies highlighting femtomolar detection limits in point-of-care diagnostics and biosensing/bioprobe in environmental applications. Present fabrication challenges including throughput scalability, material heterogeneity, and system integration will be addressed. The precision nanofabrication technique with the functionality of embedded sensing, these platforms are paving the way for real-time, miniaturized systems with profound implications for decentralized sensing and next-generation electronic sensing/ detection devices.

Prof. TomoakiMashimo

Okayama University, Japan

Bio.: TOMOAKI MASHIMO received the Ph.D. degree in mechanical engineering from Tokyo University of Agriculture and Technology, Japan, in 2008. He was a Robotics Researcher with the Robotics Institute, Carnegie Mellon University, Pittsburgh, USA, from 2008 to 2010. After being an Assistant Professor (tenure-track) with the Toyohashi University of Technology, Japan, in 2011, where he became an Associate Professor, in 2016. He is currently a Professor with the Graduate School of Natural Science and Technology, Okayama University, Japan. His research interests include piezoelectric actuators and robotic applications.

Title: Micro Ultrasonic Motors and Their Applications

This talk will present the development of millimeter-scale ultrasonic motors and their applications. Our research has successfully achieved practical levels of torque generation from these miniature motors. Recently, we have begun exploring their applications in microrobotics. The presentation will cover the driving principles and methods of our proposed micro ultrasonic motors. We will also detail the process and key ideas involved in miniaturizing these motors while simultaneously increasing their torque output. Furthermore, the talk will show examples of robot development using tiny-scale 3D printing, demonstrating the potential of these compact motor technologies.

Prof. Akio Yamamoto

The University of Tokyo, Japan

Bio.: Dr. Akio Yamamoto is a Full Professor at the Graduate School of Frontier Sciences, The University of Tokyo. He obtained his Ph.D. in Engineering from the Department of Precision Machinery Engineering, The University of Tokyo, in 1999. He served as an Associate Professor from 2005 and a Full Professor from 2017 at the School of Engineering, The University of Tokyo. In 2020, he moved to the Graduate School of Frontier Sciences, where he continues to hold a Full Professor position. 

His primary research interests lie in the fields of robotics and mechatronics. Specifically, he has focused on electrostatic actuators, non-contact object handling, and haptic devices. Dr. Yamamoto's significant contributions to these areas have been recognized in many awards, including the Best Automation Paper in IEEE ICRA 2006, the Best Paper Prize in IFAC Mechatronics Journal, and The 8th Nagamori Award from Nagamori Foundation.

Title: Electrostatic Film Actuators: Shaping the Future of Flexible Systems and Interactive Devices

Electrostatic film actuators, utilizing thin, flexible film electrode substrates, offer a unique combination of high force and inherent flexibility, making them a powerful candidate for next-generation robotic actuators. Their material versatility even allows for transparent designs, which open up novel application possibilities, particularly in human-computer interaction. While their fundamental principles have been known for over three decades, their inherent features and performance still stand out. This keynote will explore the fundamental principles and unique applications of these actuators. The talk will highlight their potential as artificial muscles for robotics and in human-machine interaction devices, alongside innovative uses like paper sheet handling, dynamic 3D paper morphing, and the integration of sensing capabilities.

Prof. Chao Gao

Zhejiang University, China

Bio.: To be updated...

Title: To be updated...

To be updated...