Prof. Wu CHEN (Conference Chair)
Head of LSGI, Chair Professor of Satellite Navigation, Hong Kong Polytechnic University
Prof. Wu Chen joined the Hong Kong Polytechnic University in 2000 and currently is the chair professor at Department of Land Surveying and Geoinformatics, Hong Kong Polytechnic University. He has been actively working on GNSS related research for over 30 years and has been working on a large number of research projects funded by universities, governments, and industries. His main research interests are Geodesy and Geodynamics, Seamless positioning technologies, indoor positioning, navigation and integrity, GNSS positioning and applications, system integration, GNSS performance evaluation, regional GPS network, wireless sensor network positioning, and Airborne Lidar applications. He has published over 300 technical papers in different journals and international conferences, submitted over 30 technical reports to various organizations, granted or filed more than 10 patents.
Prof. Xiaoli DING
Chair Professor of Geomatics & Director of the RILS, Hong Kong Polytechnic University
Prof Ding received the B.Eng. degree from the Central South University of Metallurgy, Changsha, China, in 1983 and the Ph.D. degree from the University of Sydney, Sydney, N.S.W., Australia, in 1993. He is currently the Chair Professor of geomatics and the Director of the Research Institute for Land and Space (RILS), The Hong Kong Polytechnic University, Kowloon, Hong Kong. He has lectured at the Northeast University of Technology, Shenyang, China (in 1983–1986) and the Curtin University of Technology, Perth, W.A., Australia (in 1992–1996), before joining The Hong Kong Polytechnic University in 1996. His main research interests are in developing technologies for studying ground and structural deformation and geohazards, with a current focus being upon spaceborne geodetic technologies such as GPS and InSAR.
Topic: Applications of AI in Geomatics Education at PolyU
Prof. Jean-Philippe GASTELLU-ETCHEGORRY
Professor, Center for the Study of the Biosphere from Space (CESBIO), CNRS-CNES-IRD-INRAE-Université de Toulouse
Prof. Jean-Philippe Gastellu-Etchegorry's work is focused on radiative transfer modeling with applications focused on forestry, agriculture and urban landscapes to vegetation . Since, 1992, I head the team that develops the DART model (https://dart.omp.eu) that simulates the radiative budget, including fluorescence, and remote sensing observations (satellite /airborne / in-situ spectroradiometer and LIDAR) of natural and urban landscapes. DART has become the most comprehensive model used in the remote sensing domain. It was patented in 2003. UT3 had distributed 460 licenses to research and space centers (CNES, ESA, NASA, etc.). I acted as a remote sensing expert with World Bank, FAO/United Nations and European Space Agency. I head(ed) and participate(d) in numerous projects with strong modeling and remote sensing components: ESA (Hyperspectral "Red Edge" and "HYPOS", "Fire"), European Community (UrbanFluxes: http://urbanfluxes.eu/), CNES (LiDAR, Hyperspectral). I wrote 172 papers (rate A), 8 invited communications and 7 books and book chapters (https://www.researchgate.net/profile/Jean-Philippe_Gastellu-Etchegorry/publications). I am co-chair of the Modeling in Remote Sensing Technical Committee (MIRS TC) of IEEE and Executive editor in chief of the Journal of Remote Sensing.
Prof. Bin JIANG
Professor, Urban Governance and Design Thrust, The Hong Kong University of Science and Technology (Guangzhou)
Dr. Bin Jiang is Professor of Urban Informatics in Urban Governance and Design Thrust at The Hong Kong University of Science and Technology (Guangzhou) (HKUST(GZ)). He received his PhD in GeoInformatics from Utrecht University, the Netherlands in 1996, and conducted ten-month Postdoctoral Research at Free University of Berlin, Germany. He has been Professor of GeoInformatics at University of Gävle, Sweden since April 2007. From February 2006 to September 2008, he worked as Assistant Professor at The Hong Kong Polytechnic University. He became Docent at the Royal Institute of Technology (KTH at Stockholm) in November 2005. From January 2000 to October 2005, he was Senior Lecturer at University of Gävle, Sweden. Prior to that and during January 1997 to December 1999, he was Senior Research Fellow at Center for Advanced Spatial Analysis of University College London, UK. He used to be Visiting Professor of the University of Vienna, Austria (2016), Tokyo Institute of Technology, Japan (2012), University of Sassari, Italy (2012), and Louis Pasteur University, France (2005). His research interests center on georeferenced big data, geospatial analysis, and AI/deep learning, not only for better understanding city structure and dynamics, but also for effectively transforming cities to be living or more living towards a sustainable planet.
Topic: From Geomatics to Urban Informatics: Experiential Learning for Human-Centered Design with AI
Urbanization in the AI era demands new ways of thinking about how we design, manage, and inhabit cities. This talk introduces an experiential learning approach to human-centered urban design, framed within the emerging discipline of Urban Informatics. The approach builds on the theory of living structure, which conceptualizes the built environment as a hierarchy of nested, coherent centers that foster human well-being, and integrates it with AI-powered methods such as pattern recognition, generative design, and multi-modal data fusion. By engaging students directly in hands-on projects—ranging from mapping and modeling urban spaces to experimenting with AI-assisted design evaluation—we cultivate both analytical rigor and aesthetic sensitivity. Such experiential learning not only strengthens technical competence in geomatics and informatics but also nurtures an intuitive understanding of structural beauty, spatial coherence, and their contributions to health, creativity, and community. The talk argues that “living structure + AI” inspired design can serve as a transformative paradigm for education and practice: one that transcends disciplinary boundaries, empowers learners to become co-creators of more livable cities, and aligns with global agendas such as the UN Sustainable Development Goals and the New Urban Agenda. Through case studies, pedagogical reflections, and student work, I will demonstrate how experiential learning can bridge geomatics, design, and governance in shaping a more human-centered urban future.
Prof. Yan LIU
Professor, Department of Geography and Resource Management, The Chinese University of Hong Kong
Professor Yan Liu is Professor of Geographical Information Science at the Chinese University of Hong Kong, and an Honorary Professor at the University of Queensland, Australia. She is a Quantitative Human Geographer and Spatial Data Scientist, specialising in GIS, spatial analytics and modelling, and spatially integrated social science research. Her research has broad impact on government policies and professional practices at local, national and international levels in relation to city development, urban planning, habitat conservation, social equality, and healthcare policies. She has been recognized as amongst the World’s Top 2% Scientists by Stanford University. She is a Fellow of the Royal Geographical Society (UK), an Executive Member of the IGU Applied Geography Commission and of the Computational Social Science Lab at CUHK, and served at the College of Experts of the Australian Research Council. She also serves as Associate Editor of Computational Urban Science, and an editorial board member of Computers, Environment and Urban Systems, and Environment and Planning B: Urban Analytics and City Science.
Topic: GeoAI in and for Geomatics education: An Australian perspective
Globally, Artificial Intelligence (AI) is redefining higher education, creating a paradigm filled with both significant potential and considerable challenges. In Australia, an increasing number of universities are integrating AI and related technologies, such as digital twins, into their academic programs, driving a notable trend towards Geospatial Artificial Intelligence (GeoAI). In this talk, I will share my observations on how Australian institutions are implementing GeoAI, both in Geomatics curricula as a core subject and for education as a pedagogical tool. I will discuss the observed effects, navigate the pressing challenges faced, and critically reflect on the future trajectory of this exciting field.