Prof.Dan Zhang
(Keynote Speaker)

Hong Kong Polytechnic University, HKSAR, China
Fellow of Canadian Academy of Engineering, ASME Fellow

Title of the speech: New Generation Robotics System Design and Innovation Mechanisms

Abstract: With the rapid development of technologies such as computers and artificial intelligence, we have conducted innovative designs in robotics. These innovations include dexterous hands, humanoid robot legs, one of the core components of robots: integrated joint motors, and drone landing gear, all of which have the ability to autonomously adapt to complex environments. The embodied intelligence's perception, learning, and decision-making capabilities endow these robots with stronger execution abilities. The deep integration of these aspects will propel robots from "passive execution" to "active adaptation." This presentation will introduce the achievements of our laboratory in the fields of technological innovation and application.

Brief Bio: Professor Dan Zhang is a Chair Professor of Intelligent Robotics and Automation, and Director of PolyU-Nanjing Technology and Innovation Research Institute, Director of Consortium for Intelligent Robotics Research at the Hong Kong Polytechnic University. He received his PhD in Mechanical Engineering from Laval University, Canada in 2000. He joined Ontario Tech University (OTU), Canada, as Assistant Professor in 2004 and was promoted to Associate Professor and Professor in 2006 and 2011 respectively. During the appointment period in OTU, he also served as Founding Chair in the Department of Automotive, Mechanical and Manufacturing Engineering (2012 – 2014) and was awarded the Canada Research Chair in Advanced Robotics and Automation (2009 – 2015). Since 2016, he transferred to York University, Canada as a Kaneff Professor and also took up the role of Department Chair in the Department of Mechanical Engineering from 2016 to 2018. Thereafter, he was awarded the Tier 1 York Research Chair in Advanced Robotics and Mechatronics in 2017.

Professor Zhang's research interests include synthesis and optimization of parallel and hybrid mechanisms; generalized parallel mechanisms research; reconfigurable robots; innovation design of parallel robots: parallelization of serial robots; micro/nano manipulation and mems devices (e.g., sensors); rescue robots; smart biomedical instruments (e.g., exoskeleton robots and rehabilitation robotics); AI/robotics/autonomous systems; Aerial and Underwater Robotics; Artificial Intelligence for Robotics; intelligent reconfigurable adaptive landing gear and manipulator (manipulander).

Professor Zhang is a well-accomplished educator and an internationally renowned expert in the areas of parallel robotic machines and their applications in manufacturing systems. His influential scientific contributions have led to novel robotic system designs and development of new comprehensive models for better understanding of globe stiffness and robotic calibrations. His research applications have tackled some of the world's most challenging problems in high dynamic performance manufacturing robotic systems. His leadership has resulted in significant contributions to the areas of robotics, mechatronics, reconfigurable/sustainable manufacturing systems and MEMS devices. His accomplishments have been recognized by many honors and awards including Canada Research Chair, Research Excellence Awards, Tier 1 York Research Chair, Lassonde Innovation Awards --- Established Researcher, Early Researcher Award by Ministry of Research and Innovation, Fellow of the Canadian Academy of Engineering (CAE), Fellow of the Engineering Institute of Canada (EIC), Fellow of the American Society of Mechanical Engineers (ASME) and Fellow of the Canadian Society for Mechanical Engineering (CSME).

Professor Zhang has published 296 journal papers and 193 conference papers, 12 books, 9 book chapters and numerous other technical publications. Professor Zhang has served as a General Chair for 82 International Conferences and delivered 136 keynote speeches. Professor Zhang is listed as the World’s Top Two Percent Researchers by Stanford’s Standardized Citation Indicators in 2020, 2021, 2022, 2023 and 2024.

Prof. Mohd Hamdi Bin Abd Shukor
(Keynote Speaker)

Universiti Malaya, Malaysia

Title of the speech: From Fundamental Research to Automated Solutions: Developing Advanced Engineering Devices

Abstract: The Centre of Advanced Manufacturing and Material Processing (AMMP), University of Malaya, is bridging the gap between fundamental research and practical application through the development of innovative, automated engineering devices. Stemming from earlier research initiatives, this work focuses on precision and specialized machines designed to enhance efficiency and productivity. Key developments include modular CNC lathe and gantry machines, integrated with a smart lubrication system, tailored for educational purposes and use in small and medium enterprises. The Automated Thermo-Cyclic Dipping Machine, a specialized apparatus for automated thermal testing of dental materials, exemplifies successful commercialization and is currently utilized in dental research facilities nationwide. Furthermore, the development of a Micro-pulsed Jet Minimal Quantity Lubrication system addresses lubrication challenges in metal cutting, while a novel Powder-based Physical Vapor Deposition system advances thin film deposition techniques. These projects demonstrate a successful transition from research and development to commercial realization, overcoming the challenges often associated with translating research into tangible, automated solutions.

Brief Bio: Professor Hamdi earned his Bachelor of Engineering (Mechanical) degree from Imperial College London and a Master of Science in Advanced Manufacturing Technology and Systems Management from the University of Manchester Institute of Science and Technology, UK. He further pursued his Doctor of Engineering degree at Kyoto University, Japan, under the prestigious Japanese government scholarship (Monbusho).

His academic career began in 1995 at Universiti Malaya (UM), where he advanced through the ranks, being promoted to Associate Professor in 2006, Full Professor in 2010, Senior Professor in 2014, Senior Most Professor in 2019, and ultimately Distinguished Professor in 2021.Professor Hamdi served as the Dean of the Faculty of Engineering at UM from 2009 to 2011 and later became the Deputy Vice-Chancellor (Academic and International) from 2011 to 2014. In 2019-2020, he was seconded to Universiti Kebangsaan Malaysia (UKM) as Vice-Chancellor before returning to UM, where he held the position of Vice-Chancellor until 2023.

Currently, Professor Hamdi is a board member and Vice President of the International Association of Universities (IAU), an organization under UNESCO. He also serves on the Board of Directors of PICORP LTD, a publicly listed company in Malaysia, as well as sits on the Board of Trustees of The University of Sharjah, UAE. His past roles include board memberships with the Board of Engineers Malaysia (BEM), the Institution of Engineers Malaysia (IEM), the Association of Pacific Rim Universities (APRU), the Association of Commonwealth Universities (ACU), and the ASEAN University Network (AUN). He was the chairman of the Board of Directors for METEOR Group as well as the UKM Holding. He currently sits on the Board of Zecttron Sdn Bhd, a spin off company.

Prof. Kai Cheng

Brunel University, UK

Brief Bio: Professor Cheng has had a distinguished career in manufacturing science and engineering, with extensive academic and research contributions.Appointed Chair Professor in Manufacturing Systems and Head of the Advanced Manufacturing & Enterprise Engineering Department at Brunel University London in May 2006, he built his expertise through work with UK and European industries and international institutions. His academic journey began at Harbin Institute of Technology, where he earned a BEng (Hons) 1st class (1983) and MSc Distinction (1988), later serving as an assistant lecturer and lecturer (1983–1990). He pursued a PhD and postdoc with Professor Brian Rowe at Liverpool John Moores University (1990–1995), followed by roles as senior lecturer at Glasgow Caledonian University (1995–1999), reader (1999), and professor (2001) at Leeds Metropolitan University. He became a Chartered Engineer (2000), and a Fellow of IET (2004) and IMechE (2006).

His work focuses on ultraprecision and micro/nano manufacturing, including ultraprecision machines, machining science, and smart cutting tools. At Brunel, his team collaborated with UK industries via dozens of EPSRC, Innovate UK, and EU projects over two decades, benefiting over 50 British companies. Currently leading Brunel’s Micro/Nano Manufacturing Theme (15 academics, 50 PhD students), he has led 35 UK/EU projects, securing over 30 million Euros in grants. He holds 12 patents, authored 280 publications, supervised 60+ PhDs, and has an H-index of 52. His accolades include the 2016 ASME BOSS Award.

Active in academic leadership, he is European Editor for the International Journal of Advanced Manufacturing Technology and serves on five other editorial boards. Since 2016, he has given over 20 keynote speeches at international conferences by ASME, IEEE, etc.(More)

Prof. Ruqiang Yan

IEEE Fellow

Xi'an Jiaotong University, China

Title of the speech: From Data-Driven to Knowledge-Embedded: Redefining the Future of Predictive Maintenance

Abstract: Predictive maintenance relies critically on accurate degradation assessment and remaining useful life (RUL) prediction of complex equipment. While deep learning has achieved impressive progress in this domain, traditional data-driven methods still suffer from inherent weaknesses: dependence on large volumes of labeled data, vulnerability to noise, and poor adaptability under distribution shifts. These challenges limit their generalization and hinder practical deployment in real-world industrial environments.

This keynote introduces a paradigm shift from purely data-driven to knowledge-embedded deep learning. By embedding domain expertise, degradation mechanisms, and physical insights into neural networks, we can overcome the shortcomings of conventional approaches, leading to models that are more robust, interpretable, and effective under diverse data conditions.

The talk will introduce recent advances in knowledge-embedded deep networks for RUL prediction, highlighting three representative scenarios—abundant data, limited data, and no degradation data—together with corresponding strategies such as similarity matching, regression-based learning, and time-series modeling. Case studies, including wind turbine bearing RUL prediction, will demonstrate how knowledge embedding significantly enhances generalization, accuracy, and stability. Finally, the keynote will explore emerging opportunities and future directions, emphasizing how knowledge-embedded intelligence can bridge the gap between engineering expertise and artificial intelligence, and redefine predictive maintenance for complex systems.

Brief Bio: Ruqiang Yan received the M.S. degree in precision instrument and machinery from the University of Science and Technology of China, Hefei, China, in 2002, and the Ph.D. degree in mechanical engineering from the University of Massachusetts at Amherst, MA, USA, in 2007.

He was a Guest Researcher at the National Institute of Standards and Technology (NIST) in 2006-2008 and a Professor with the School of Instrument Science and Engineering, Southeast University, Nanjing, China from 2009 to 2018. He joined the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China, in 2018. His research interests include data analytics, AI, and energy-efficient sensing and sensor networks for the condition monitoring and health diagnosis of large-scale, complex, dynamical systems.

Dr. Yan is a Fellow of ASME (2019) and IEEE (2022). His honors and awards include the IEEE Instrumentation and Measurement Society Technical Award in 2019 and Outstanding Service Award in 2022, and multiple best paper awards, such as Andrew P. Sage Best Transactions Paper Award. Dr. Yan served as the Editor-in-Chief (EiC) of the IEEE Transactions on Instrumentation and Measurement (2022-2024). He is a Distinguished Lecturer of the IEEE Instrumentation and Measurement Society and an Associate EiC of Chinese Journal of Mechanical Engineering. He will be the incoming EiC of IEEE Systems Journal starting from January 1, 2026.