ICITE2026 Keynote Speakers
Prof. Hai Yang | 杨海教授
Chair Professor, Department of Civil and Environmental EngineeringThe Hong Kong University of Science and Technology, Hong Kong, China | 香港科技大学
Professor Hai Yang is currently a Chair Professor at The Hong Kong University of Science and Technology (HKUST) and is an internationally renowned scholar in the field of transportation research. His work has been extensively published in top-tier academic journals such as Transportation Research, Transportation Science, Operations Research, and PNAS, placing his academic influence among the global forefront in the transportation field. Professor Yang has received numerous prestigious awards, including the HKUST School of Engineering Distinguished Research Excellence Award (2025), the American Society of Civil Engineers (ASCE) 2021 Francis C. Turner Award, the 2020 Frank M. Masters Transportation Engineering Award, and the 2011 State Natural Science Award presented by the State Council of China. He has been appointed as a "Changjiang Scholar" Chair Professor by the Ministry of Education of China and served as the Editor-in-Chief of the flagship journal Transportation Research Part B: Methodological from 2013 to 2018. He currently holds the position of Honorary Editorial Board Member for the journal and serves on the Scientific Committee of Transportation Research Part C: Emerging Technologies. Additionally, Professor Yang is an Advisory Editor for Transportation Science and a Co-Editor-in-Chief of AI for Transportation.
Speech Title: Building Urban Air Mobility: Technology, Policy, and Public Perception in China's Greater Bay Area
Abstract: The low-altitude economy, powered by drones and eVTOL aircraft, is reshaping urban transport, logistics, and public services. This presentation examines its development prospects along three dimensions. First, it introduces core concepts and global growth potential, focusing on market opportunities in Mainland China and Hong Kong, along with key technological foundations and adoption barriers. Second, it showcases our team's drone solutions for urban inspection, environmental monitoring, and parcel delivery, demonstrating how drone technology enhances urban management and supports smart cities. Third, drawing on findings from a Strategic Public Policy Research Project on advanced air mobility in the Guangdong–Hong Kong–Macao Greater Bay Area, we integrate stakeholder interviews and large-scale user surveys. This evidence-based approach identifies regulatory and infrastructural gaps, examines enterprise strategies and customer perceptions, and proposes actionable policy recommendations to facilitate government–enterprise collaboration and foster sustainable growth of the low-altitude economy in the region.
Prof. Lixi Huang | 黄立锡教授
Deputy Head of Department of Mechanical EngineeringThe University of Hong Kong, Hong Kong, China | 香港大学
Lixi was educated at Beijing Institute of Aeronautics (now BUAA or Beihang Univ.) and University of Cambridge. His BEng and MPhil degrees from BUAA were in the field of aerospace engineering (jet propulsion), while the topic of his PhD study at Cambridge was theoretical acoustics and respiratory biomechanics. He spent 8 years each in Beijing and Cambridge before coming to Hong Kong in 1996. After completing his PhD work in 1991, he worked as a research associate at the Whittle Lab (of turbomachinery), then as a college research fellow at Peterhouse, both within the University of Cambridge. His work on the mechanism of human snoring helped his medical/surgical colleagues devise a successful laser surgery procedure in the early 1990s, and the related pursuit in fluid mechanics touched upon the fundamentals of fluid-structure energy transfer mechanisms. Before joining the University of Hong Kong in 2006, he taught at HK PolyU Mechanical Engineering and served as a leader for the teaching group of acoustics and vibration. In the last decade or so he has been working in industrial and environmental noise control with a special focus on the use of electromagnetic forces in acoustics. His research projects have been funded by the Hong Kong Government funding agencies (RGC, ITF), industry, and mainland sources (“973” projects, and Department of Science and Technology, Zhejiang Province, PRC).
His current research interests are (a) aerodynamics and acoustics with application to aeronautical and general engineering, (b) innovative broadband noise control with applications to environmental noise, and (c) flow induced vibration and interaction with sound.
He currently serves as a subject editor for Journal of Sound and Vibration, an associate editor for the Journal of the Acoustical Society of America, and an editorial board member for Chinese Journal of Acoustics.
Speech Title: Sonic Black Hole and Its Sound Absorption Performance
Abstract: Over the past two decades, acoustic retarding structures, analogised to sonic "black holes" (SBH), have garnered significant attention for their potential to achieve perfect sound absorption. Typical designs feature annular rings with progressively smaller radii designed to bring sound waves to rest at zero radius. Yet these structures still reflect significant sound, a flaw widely attributed to the engineering impossibility of achieving a true zero radius with infinite acoustic admittance. In this talk, we re-examine the analytical solution for a typical SBH configuration and conclude that sound waves cannot be trapped by slowing down to zero phase speed. We attribute this impossibility instead to the breakdown of the approximate side-wall boundary condition used in the original theory. When an accurate boundary condition for the configuration is used, and yet the fluid viscosity is ignored, the phase speed is found to increase instead of decrease. This result contrasts with what the astronomical term of black-hole may reasonably imply. With such clarifications, our focus is shifted to the practical performance of such a retarding structure, renamed as "cylindrical waveguide with impedance gradient" (CWIG), for broadband sound absorption. For a pink incident noise, it is found that CWIG with a theoretical anechoic terminal performs similarly to a traditional acoustic wedge but CWIG with practically optimized gradual damping may provide good performance comparable to an array of Helmholtz resonators.
Prof. Chengzhong XU | 须成忠教授
IEEE FellowUniversity of Macau, Macau SAR, China | 澳门大学
Dr. Cheng-Zhong Xu is a Chair Professor of Computer Science and the Dean of the Faculty of Information Science and the Director of the Institute of AI and Brain Sciences, University of Macau. He served as Chief Scientist for key national projects on “Internet of Things for Smart City” (Ministry of Science and Technology of China) and “Intelligent Driving” (Macau SAR, China). He was also Director of Institute of Advanced Computing and Digital Engineering at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences. Before these roles, he spent over 18 years as a faculty member at Wayne State University, USA. Dr. Xu's research focuses on parallel and distributed systems, cloud computing, intelligent driving and smart city applications. He has published over 600 papers and held more than 150 patents. His work has garnered over 29000 citations and has been cited in 340+ international patents, including 240 U.S. patents. Dr. Xu chaired IEEE Technical Committee of Distributed Processing from 2014 to 2020. He earned his B.S. and M.S. in Computer Science from Nanjing University and his Ph.D. from the University of Hong Kong in 1993. He is an IEEE fellow, due to contributions in resource management in parallel and distributed systems.
Speech Title: World Models for Robust Autonomous Driving in Mixed Traffic
Abstract: Autonomous driving is transitioning into a mature phase focused on robustness, leveraging cognitive edge AI technologies. This talk will first discuss the challenges for robust autonomous driving in mixed traffic where self-driving and human driving vehicles co-exist. It will then introduce University of Macau’s MoCAD project, which develops core enabling technologies for robust autonomous driving in open and complex environments. Topics of generated AI for creating robust scenarios and world models for end-to-end driving simulation will be presented. Occupant emotional states and surrounding traffic behavior will also be discussed, as self-driving vehicles become moving robots on the road.