Chi Fai Benny Cheung

State Key Laboratory of Ultra-precision Machining Technology 
Department of Industrial and Systems Engineering
The Hong Kong Polytechnic University

Ir Professor Benny C.F. Cheung is the Chair Professor of Ultra-precision Machining and Metrology at the Department of Industrial and Systems Engineering, Director of State Key Laboratory of Ultra-precision Machining Technology, The Hong Kong Polytechnic University. He is also a Fellow of the International Academy for Production Engineering (CIRP Fellow), the International Academy for Engineering and Technology (AET Fellow), and a College of Fellow of the American Society for Precision Engineering (ASPE College of Fellow). His main research interests include ultra-precision machining, precision metrology and smart precision manufacturing. Up to present, he has authored and co-authored more than 300 SCI/SSCI indexed refereed journal papers. He received many research prizes and awards including 2008 ASAIHL-Scopus Young Scientist Awards – First Runner Up Prize in the category of “Engineering and Technology”, Joseph Whitworth Prize 2010 and A M Strickland Prize 2017 by The Institution of Mechanical Engineers, UK, Bank of China Hong Kong Science and Technology Innovation Prize 2023. – Advanced Manufacturing, etc.

Abstract: Semiconductor wafer manufacturing is a highly time-sensitive precise industry that requires strict process control to meet stringent dimensional tolerances. The surface topography of wafers exhibits significant multi-scale characteristics. At the macroscopic scale, it manifests as deviations in overall flatness. At the mesoscale, it manifests as fluctuations in local waviness, and at the microscale, it manifests as surface roughness as well as local defects such as scratches and pits. These multi-scale morphological characteristics influence key processes. In this presentation, a non-destructive smart testing and inspection technology for semiconductor SiC wafers is presented for multi-scale surface measurement and defect characterization in  manufacturing of SiC wafers. Hence, a multi-mode non-destructive smart detection system is established based on variable-scale shear interferometry, super-resolution machine vision microscopy, intelligent extraction and quantitative characterization of global defects and sub-surface defects. The system offers high lateral resolution and sufficient sensitivity to measure nanoscale topography and surface roughness by acquiring a single snapshot of the wavefront phase image. It innovatively integrates microscopy and beam expansion into a single optical path. Through a built-in mirror switching mechanism, it can flexibly switch between high-precision microscopy and a wide field of view, achieving a balance between compactness and versatility.

Ömer Sahin Ganiyusufoglu

Qingdao International Academician Park

Prof. Ganiyusufoglu is member of German National Academy of Science and Engineering (acatech), advisory professor of Tongji University, Honorary Professor of Nanjing University of Aeronautics and Astronautics, Yantai University and Zhejiang University for Science and Technology.  
In 2018, he got Friendship Award, the highest Award of Chinese Government for a foreigner. He also received awards of Dalian City, Shenyang City and Liaoning Province. 
Born 1954 in Istanbul/ Türkiye, he is German Citizen, since 2006 resident in China. 1979, he graduated from Technical University Berlin. 1984, he got the Doctor Degree from IWF - Institute for Machine Tools and Manufacturing at Technology of TU Berlin. 
He worked as department manager for systems technology of Traub AG (Germany), as Managing Director at Yamazaki Mazak Germany (Japanese family-owned machine tool manufacturer) and General Manager of Index Dalian Machine Tool Ltd (Joint venture between Index-Werke Germany and Dalian Machine Tool Group, Resident in Dalian).
2017 to 2019, he was elected as Chairman of Corporate Members Advisory Group CMAG within CIRP – International Academy for Production Engineering. 
2011 to 2020, he was the Consultant to Chairman of Shenyang Machine Tool Group Co., Ltd (Resident in Shenyang). 
Since 2021, he is Industrial Development Consultant of Qingdao International Academician Park (QIAP)

Abstract: The traditional manufacturing technologies of our time have reached their limits. Electronics are advancing at an ever-increasing pace. The growing miniaturisation in electronics and the advent of quantum computing are opening up new possibilities.
Conventional subtractive and additive manufacturing methods are no longer capable of realising innovations in line with the new possibilities offered by electronics.
On the other hand, humanity needs innovation in many areas for the future to make life better, safer and more interesting.
ACSM – Atomic and close-to-atomic scale manufacturing – is a welcome method for breaking new ground in technology and enabling innovation. For example, new, intelligent materials can be developed, and methods in medical technology that are still unimaginable today can be devised, enabling people to lead healthy, perhaps even longer, happy lives.

Wanlin Guo

State Key Lab of Mechanical Structural Mechanics and Control
Key Lab of  Intelligent Nano Materials and Devices of MOE
International Institute for Frontier Science of Nanjing University of Aeronautics and Astronautics
Nanjing University of Aeronautics and Astronautics
 

Wanlin Guo, an academician of the Chinese Academy of Sciences, a professor at Nanjing University of Aeronautics and Astronautics, and the Dean of the International Institute for Frontier Science. Professor Guo Wanlin has long been engaged in research on digital science and intelligent technology for aerospace, hydrovoltaic science and technology, and physical mechanics. His current research focuses on hydrovoltaic energy, ecology and intelligence; quantum biophysical mechanics; intelligent nanomaterials and devices; and structural strength, durability and reliability. In 2012 and 2024, he twice received the Second Prize of the National Natural Science Award of China as the leading recipient. In 2013, he received the Xu Zhilun Mechanics Prize. In 2019, he was awarded the Ho Leung Ho Lee Foundation Prize for Scientific and Technological Progress and the Eric Reissner Award in International Mechanics. In 2020, he was honored with the title of National Advanced Worker.

Abstract: This report starts from the wisdom of living beings in acquiring energy for survival, extends to the understanding of natural intelligence and brain functions, and then to the frontier progress and challenges of artificial intelligence. Furthermore, based on the relationship between water and life, as well as water and energy, it proposes the concept of hydrovoltaic intelligence: exploring how the synergy of 'intelligence' and 'energy' can lead the future development of science, technology, and human civilization.
Living beings have intelligence. The unicellular organisms formed between 3.5 billion and 4.1 billion years ago in water can obtain energy from the environment for surviving, show living intelligence. After billions of years of evolution, our human beings developed the intelligence for learning, reasoning, problem solving as well as thinking. It is widely recognized that human intelligence lies in the complex neuron networks in our brain, which containing more than 70% of water, working at energy consumption about 20 W.
“Can machines be as intelligent as human in game?”  Turing raised the question in 1950, leading to the come of artificial intelligence (AI), which is also inspired by the neuron networks found in our brain. Now, machines can be as “intelligent” as human in games, but at huge energy consumption. Data center is always electricity hungry, not like our brain, the Nature intelligence (NI). 
Our hierarchical modeling and non-linear dynamics analysis show that our brain can store and process huge information at energy consumption ~1.26 times of the theoretical limitation, about more than 8 orders of energy efficient than the most advanced AI chips1. 
We have shown that electricity can be generated from the direct interactions of materials with water through hydrovoltaic effects, such as waving potential, drawing potential, evaporating potential, leading to the emerging hydrovoltaic technology2-6 and hydrovoltaics: New ways of harvesting electricity from water.
Here, we will briefly review the recent advances in AI technology as well as hydrovoltaics for harvesting environmental energy, serving as a potential Negative thermal emission energy technology, and discuss the role of confined water in our brain and envision the hydrovoltaic intelligence (HI) based on our recent findings7-10. New advances to go beyond the Turing Machine11, to go from AI to HI, will also be outlined to encourage students to develop their talent. 

Enrico Savio

Department of Industrial Engineering - Precision Manufacturing
University of Padua 

Enrico Savio is a Professor of Digital Manufacturing at the University of Padova, Italy, with a research focus on Manufacturing Metrology. Current research interests include on-machine and in-process metrology, metrology of freeform surfaces and complex parts, digital-metrological twins, and economics of measurements in industry. He is a Fellow of CIRP, in which he served as Chairman of the Scientific Technical Committee “Surfaces”; was President of euspen; in 2003, he was awarded the CIRP F.W. Taylor Medal. 
He is currently serving as President of the ISNM.

Abstract: This keynote addresses the integration of digital twins (DTs) and metrology in advanced manufacturing applications. DTs enable real-time synchronization between physical systems and their virtual representations, supporting enhanced monitoring, predictive modeling, and process control. The continuous acquisition of measurement data enables dynamic model updates, improving process optimization, particularly in small-batch and high-variability production.
However, significant challenges remain. Reliable measurements in harsh environments and on complex surfaces are challenging, as measurement uncertainty directly affects system performance. Addressing these issues requires a multidisciplinary approach, combining advances in metrology, sensor technology, data integration, and process simulation. 
The talk will discuss key challenges and present selected application examples in manufacturing, highlighting how integrated metrology and DTs can enhance efficiency, flexibility, and decision-making in next-generation manufacturing systems.

Suet Sandy To

Department of Industrial and Systems Engineering
State Key Laboratory of Ultra-precision Machining Technology
The Hong Kong Polytechnic University 

TO Suet is a Professor in the Department of Industrial and Systems Engineering of the PolyU, an Associate Director of the State Key Laboratory of Ultra-precision Machining Technology and Advanced Optics Manufacturing Center, and Director of PCB and Functional Materials Characterization Laboratory. She is a Committee Member of the Asian Society for Precision Engineering and Nanotechnology (ASPEN), Member of the Chinese Mechanical Engineering Society (CMES), Member of The International Academy for Production Engineering (CIRP) and Fellow of Hong Kong Institution of Engineers (HKIE). She also serves as the editorial board member of several international journals. Her main research directions include research on ultra-precision machining of micro-nano structural functional surfaces; research on multi-field-assisted ultra-precision machining of difficult-to-cut materials; and smart manufacturing of ultra-precision machining technology. Prof. To has undertaken more than 20 key research projects as principal investigator. Her research outcomes are well-recognized. She has published seven research books and more than 350 international journal papers, was ranked as the World’s Top 2% most-cited scientists 2025 by Stanford University. Her research outcomes were granted the Natural Science Award and Scientific and Technological Progress Award by the Higher Education Outstanding Scientific Research Output Awards by the Ministry of Education of the PRC, as well as three times, as a supervising teacher, received the Hiwin Doctoral Dissertation Award from the Chinese Mechanical Engineering Society. Prof. To has been granted 26 patents and was invited to be the keynote or invited speaker at several international conferences.

Abstract: Ultra-precision machining technology based on single-point diamond turning (SPDT) and ultra-precision freeform machining have become an indispensable tool for the design and the manufacture of high- technology and high-precision lenses. The process is capable of producing components with micrometer to sub-micrometer form accuracy and surface roughness in the nanometer range. With the fast growing development of machining technology, ultra-precision machining technology is used not only for manufacturing symmetrical spherical and aspheric workpieces, but also to produce some very complex and non-symmetrical microstructures.
This presentation mainly introduces Professor To’s research team research achievements in the field of ultra-precision machining. These include the study of ultraprecision machining and the combination of physical energy fields such as magnetic fields, ultrasonic, laser, and electric fields on difficult-to-machine and hard and brittle materials, as well as the theory and methods of ultraprecision machining of micro/nano structures.