2026 Speakers
Prof. Mingwang Fu
Hong Kong Polytechnic University, China
Biography:
Mingwang Fu (MW Fu), PhD, is the Chair
Professor of Advanced Manufacturing at the
Hong Kong Polytechnic University. He is
leading the Joint Research Centre for Design
& Net-shape Forming of Surface Functional
Structures and is an Associate Director of
the Research Institute for Advanced
Manufacturing. He is a fellow of the Society
of Manufacturing Engineers (SME), the Hong
Kong Institution of Engineers, and a Royal
Society Wolfson Visiting Fellow. He
published over 350 journal papers, 7
monographs (three of which are the
first-ever in their respective fields), and
one volume in the Elsevier Encyclopedia of
Materials, with an H-index of 72. Recently,
MW was awarded (1) the SME Frederick W.
Taylor Research Medal (2026) for his
outstanding contributions to manufacturing
science; (2) the Khan International Award
(2026) for his pioneering research and
lifelong outstanding contribution to the
plasticity/damage/fracture of materials
(2026); and (3) LEE HSUN Research Award
(2025) for his unique contributions to
materials science and engineering.
MW’s research is unique in its breadth,
depth, and originality, characterized by a
vital mastery of modelling and numerically
esoteric mathematics, including the
numerical solution of high-order
differential equations. Its complexity and
difficulty are also highlighted by non-linearities
arising from material aspects, including
viscoplasticity, large-scale and non-uniform
deformation, anisotropy and asymmetry, as
well as by the non-linearities of geometries
involved in design and manufacturing.
Prof. Hirotaka Sato
Nanyang Technological University, Singapore
Biography:
Hirotaka Sato is a Professor in the School of Mechanical and Aerospace Engineering at Nanyang Technological University (NTU), Singapore. He received his BEng, MEng, and PhD in Chemistry from Waseda University, Japan. His research focuses on insect-machine hybrid robots (cyborg insects), integrating miniaturized electronics with living insects for search-and-rescue applications in complex environments. His team pioneered automated assembly, swarm navigation, and adaptive locomotion technologies for bio-hybrid robots. His work has been published in leading journals such as Nature Communications and npj Robotics and featured by major international media. His research was recognized by TIME as one of the "50 Best Inventions of 2009" and by MIT Technology Review in its "TR10" list. He currently serves as an NTU Senator and has received multiple honors, including the NTU Provost's Chair (2019–2025) and the 2025 Pineapple Science Award.
Prof. Ching-Chi Hsu
National Taiwan University of Science and Technology, Taiwan
Biography:
Ching-Chi Hsu is a Professor in the Department of Mechanical Engineering at National Taiwan University of Science and Technology, Taiwan. His research interests include explicit dynamics analysis, thermal-structural coupling analysis, computational biomechanics, medical image processing and digital sculpt modeling, intelligent optimization algorithms and programming, and experimental methods for static and fatigue testing. He has applied computational mechanics to the development of various industrial products, achieving meaningful integration of industrial needs and academic research. His recent work includes orthopedic implant design and development, impact on human skeletal structures and protection strategies, computationally driven microstructural optimization for additive manufacturing, semiconductor sensors and equipment design and development, and analysis of thermal runaway behavior in lithium‑ion battery structures.
Assoc. Prof. Hiroyuki Kodama
Kindai University, Japan
Biography:
Hiroyuki Kodama is an Associate Professor in the Department of Mechanical Engineering, Faculty of Science and Engineering, Kindai University, Japan. His research focuses on data-driven machining and intelligent manufacturing, particularly process monitoring, tool wear detection, machining state diagnosis, and optimization of cutting conditions. He has developed methods for analyzing machining process data obtained from servo motor current signals, spindle load data, cutting force signals, and chip images by using data mining and machine learning techniques. His recent work aims to establish interpretable manufacturing systems that support decision-making in machining processes through the integration of sensing data, image information, and manufacturing knowledge. His broader research interests include smart manufacturing, cutting process monitoring, manufacturing data analysis, and human-centered decision support for production systems.