Keynote Speaker I
Biography: Junzhi Yu (Fellow, IEEE) received the BE degree in safety engineering and the ME degree in precision instruments and mechanology from the North University of China, Taiyuan, China, in 1998 and 2001, respectively, and the PhD degree in control theory and control engineering from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 2003. From 2004 to 2006, he was a postdoctoral research fellow with the Center for Systems and Control, Peking University, Beijing. In 2006, he was an associate professor with the Institute of Automation, Chinese Academy of Sciences, where he became a full professor in 2012. In 2018, he joined the College of Engineering, Peking University, as a tenured full professor. His research interests include intelligent robots, motion control, and intelligent mechatronic systems.
Speech Title: Towards Safe and Trusted Embodied Intelligent Systems
Abstract: In recent years, autonomous intelligent systems (physical embodied intelligent agents) appear in many aspects of human society. How to achieve human level of reliable (safe and trusted) autonomous behavior generation still faces great challenges. This talk is based on our research experience over a decade. I will talk about autonomous behavior generation method for physical embodied intelligent agents from the perspective of machine learning, and report the latest progress we have made.
Keynote Speaker II
Biography: Professor Geoff Holmes has been a major contributor to the University of Waikato’s machine learning project which has had a far-reaching influence on developments in the field worldwide, principally through the open-source Weka software, one of the most widely used machine learning tools in the world today (Weka software has been downloaded 16.8 million times since it was first hosted at the Sourceforge website for open-source software in April 2000).
Professor Holmes has led the applied machine learning subgroup at the University for the past 20 years. This group has expertise in the deployment of machine learning solutions in practice and has developed a bespoke platform for this purpose (see https://adams.cms.waikato.ac.nz/). He has attracted major government and industry funding totaling several million dollars.
Professor Holmes has also been responsible for the development of a platform for processing very large (possibly infinite) datasets called MOA (Massive Online Analysis) see http://moa.cms.waikato.ac.nz/.
Aside from software contributions, Professor Holmes has made contributions to the major conferences in machine learning, data mining and deep learning (over 150 academic publications). He is currently working on a deep learning platform that enables data-owners to build models without the need for programming expertise or access to significant computing resources.
Professor Holmes has conducted several projects using machine and deep learning in the field of agricultural robotics. This includes yield estimation, plant pollination, disease identification and pruning vines.
Speech Title: Horticultural Robotics – a New Zealand perspective
Abstract: Horticultural produce is one of New Zealand's main exports and labour shortages are an on-going threat to the industry with many other countries facing similar problems. Robotics is perceived by many as the way to solve the labour shortage and globally a wide range of prototypes and early market robotic products have been developed. However, nearly all of them face challenges to be commercially viable. Learning from horticultural robotics examples in New Zealand, the challenges and potential ways of overcoming them are explored. Areas covered include hardware development, autonomous vehicles and safety issues, co-design methods, fast fail, alternative growing structures, fake orchards, human assist, data for orchard management, systems approach and robot modularity, closing the loop and integrating expert human decision making into horticultural robots.
Keynote Speaker III
Biography: Jing Zhou is a Professor and PhD supervisor at Zhejiang University. She serves as the Deputy Director of the Zhejiang Provincial Collaborative Innovation Center for Intelligent Ocean Technology and is a member of the Marine Technology Equipment Committee of the Chinese Society for Oceanography. Her research focuses on new concept underwater robots and their key technologies. She has led several projects, including the Original Exploration Project of the National Natural Science Foundation of China (a 3-year project) and the Zhejiang Provincial Outstanding Youth Fund. Additionally, she serves as the Deputy Chief Engineer of a key project in the Innovation Zone of the Central Military Commission Science and Technology Commission. She has published over 60 papers in prestigious journals such as Nature sub-journals and Engineering, with several of her research papers selected as ESI highly cited papers. She holds 13 invention patents in China and the United States. Her achievements have been recognized with several awards, including the Second Prize of Science and Technology Progress from the China Power Supply Society, the Third Prize of Science and Technology Progress of Zhejiang Province, and the Best Paper Award at an international conference.
Speech Title: Modular Reconfigurable Marine Robotics
Abstract: The complexity and variability of the marine environment, together with the diversity of operational tasks, require underwater robotic systems that are versatile in both function and form. While conventional single-mode robots perform well in specific scenarios, they often lack the flexibility needed for a wide range of marine activities. In contrast, modular and reconfigurable underwater robots—characterized by high adaptability and versatility—have shown prominent advantages across various applications.
Our initial modular underwater robot was designed by decomposing the system into functionally independent units. These modules can be configured and combined according to environmental conditions and operational needs, forming a series of specialized robotic systems tailored to different missions. Evolving from this concept, we have developed a building-block-style reconfigurable underwater robot that supports rapid and flexible underwater assembly into different configurations to perform diverse tasks.
This presentation will discuss key technologies enabling these systems, including mechanical structure, power distribution, and control architecture.
Keynote Speaker IV
Biography: Hamid Marvi is an Associate Professor of Mechanical and Aerospace Engineering at Arizona State University, where he also holds the Fulton Entrepreneurial Professorship and directs the Bio-Inspired Robotics, Technology, and Healthcare (BIRTH) Lab. He is a Senior Global Futures Scientist and an Alliance Fellow of the Mayo Clinic–ASU Alliance for Health Care. His research integrates materials science, robotics, and biology to develop soft and magnetic robots for medical applications. Dr. Marvi’s work has been featured in Science, PNAS, Advanced Materials, and Nature Scientific Reports, as well as in major media outlets like The New York Times and BBC. His honors include Senior Membership in the National Academy of Inventors, the 2024 ABRC New Investigator Award, the Sigma Xi Best Ph.D. Thesis Award, and multiple national awards for innovation in robotics and soft materials.