Prof. dr. Nico Van de Weghe is a full Professor of GIScience at the University of Ghent (UGent), affiliated with the CartoGIS research unit. His work bridges computer science, social science, and natural science through geospatial information studies, focusing on enabling machines to reason spatially (GeoAI). Since 2004, he has specialized in knowledge-based AI, particularly spatiotemporal reasoning and moving object analysis, with applications in animal behavior, criminology, healthcare, mobility, and sports. Van de Weghe's research emphasizes hybrid GeoAI systems combining knowledge-driven and data-driven approaches. Keywords include GeoAI, GIScience, Spatiotemporal Analysis, Moving Objects, and Data Mining. Recent publications highlight urban road network analysis, hybrid trajectory modeling, BIM semantic enrichment, and cycling safety studies using virtual reality.
Filip Biljecki is an Assistant Professor jointly appointed at the Department of Architecture within the College of Design and Engineering and the Department of Real Estate at the NUS Business School, National University of Singapore. He is the founder and principal investigator of the NUS Urban Analytics Lab and was awarded the prestigious NUS Presidential Young Professorship in 2020. With over 150 peer-reviewed publications, his research bridges geomatic engineering, geospatial technologies, and urban data science to advance digital twins and data-driven urban planning. Dr. Biljecki's educational background includes: PhD in 3D GIS (cum laude), Delft University of Technology, Netherlands (2017) MSc in Geomatics, Delft University of Technology, Netherlands (2010) BSc in Geodesy and Geoinformatics, University of Zagreb, Croatia (2008) His research interests focus on emerging urban data sources, particularly urban imagery, and their application in 3D city modeling, digital twins, and GeoAI. He explores how crowdsourcing and open science can inform cutting-edge techniques for urban sensing and analytics at city-scale. His work significantly contributes to establishing smart cities through innovative methods that integrate recent advancements in computer science, geomatics, and urban data science. Analysis of his recent publications reveals a strong focus on street view imagery applications for urban analytics, digital twin development, and geospatial AI. His research spans multiple domains including urban morphology, environmental assessment, public health applications, and urban comfort analysis. The interdisciplinary nature of his work is evident in collaborations with researchers from diverse fields, producing impactful studies that address complex urban challenges through innovative methodological approaches. His notable scientific achievements include: Annual Teaching Excellence Award (ATEA), 2025 College Educator Award AY2023/2024, 2025 Urban Informatics Paper of the Year Award, 2023 Top 2% scientists worldwide (Stanford University), 2021 Presidential Young Professorship (NUS), 2020 As an educator, Dr. Biljecki has supervised dozens of students leading to publications in leading journals and placements at top universities and organizations. He has delivered talks at over 120 universities and organizations worldwide including MIT, Stanford, Harvard, and ETH Zurich. His research is supported through various grants and affiliations including his role as Principal Investigator at the Future Cities Lab Global at the Singapore-ETH Centre. The NUS Urban Analytics Lab, which he established, brings together scholars from diverse disciplines to drive research on making cities smarter and more data-driven. The lab has developed innovative tools like ZenSVI for street view imagery analysis and has produced influential research on urban digital twins, urban morphology, and GeoAI applications. Through his leadership, the lab continues to pioneer methods that advance data-driven urban planning and smart city development.
May Yuan is the Ashbel Smith Professor of Geospatial Information Sciences at the University of Texas at Dallas (UT-Dallas), affiliated with the School of Economic, Political and Policy Sciences. She directs the Geospatial Analytics and Innovative Applications (GAIA) Lab. Her research focuses on space-time representation, GIS analytics, and environmental/social problem-solving (e.g., disaster risk, pollution, crime mapping). She holds a Ph.D. in Geography from SUNY Buffalo (1994) and B.S. from National Taiwan University (1987). Previously, she was Brandt Professor and Director of the Center for Spatial Analysis at the University of Oklahoma (1994–2014). Education: Ph.D. in Geography, State University of New York at Buffalo, 1994 M.A. in Geography, State University of New York at Buffalo, 1992 B.S. in Geography, National Taiwan University, 1987 Research Interests: Her work integrates space-time GIS databases with cognitive science, environmental modeling, and social dynamics. Key areas include: - Spatiotemporal query and analytics for geographic processes - GIS-based disaster risk assessment (wildfires, tornadoes) - Urban air quality modeling - Neurogeography and Alzheimer’s disease prediction using environmental complexity metrics - Deep mapping and spatial narratives. Grants & Partnerships: Supported by NSF, NASA, DoD, DHS, NOAA, EPA, and state agencies. Her GAIA Lab explores 'place' concepts in space-time analytics. Awards & Roles: Fellow, AAAS and AAG Editor-in-Chief, International Journal of Geographical Information Science (2017–present) Former President, Cartography and Geographic Information Society (2020–2021) and UCGIS (2011–2012) Member, NOAA Environmental Information Services Working Group (2016–2022) Labs/Teams: Leads the GAIA Lab, collaborating on geospatial AI, environmental health, and urban analytics.
Bing Zhou serves as an Assistant Teaching Professor in the Department of Geography and the John A. Dutton Institute for Teaching and Learning Excellence within the College of Earth & Mineral Sciences at The Pennsylvania State University, focusing on advancing geospatial education and research. His educational background includes: Ph.D. in Geography from Texas A&M University Dr. Zhou pioneers research in geospatial data science and GeoAI, developing advanced algorithms to extract insights from big geospatial data (crowd-sourced data, mobility data, social media) for climate resilience and disaster response. He founded the revolutionary field of Responsible GIScience, which integrates ethical principles, human values, and societal interests into geospatial research and education. His work specifically targets identifying location-based help information from social media to support disaster response in high-risk communities, aiming to build resilient, equitable, and healthy societies through responsible spatial thinking. He teaches core courses including GEOG 589: Emerging Trends in Remote Sensing and GEOG 480: Exploring Imagery and Elevation Data in GIS Applications. Information regarding scientific awards, student advising, grant funding, and laboratory teams is not documented in the provided materials.
Professor Qihao Weng is Chair Professor of Geomatics and Artificial Intelligence at The Hong Kong Polytechnic University, where he leads the Research Institute for Land and Space. A globally recognized scholar, he bridges geography, landscape ecology, and environmental science through innovative geospatial analytics, GeoAI, and big data methodologies. His work focuses on urban climatology, sustainability science, and human-environment interactions, with over 279 publications and 14 books. PhD, The University of Georgia MA, The University of Arizona MS, South China Normal University Professor Weng's research explores remote sensing applications for urban environmental challenges, including thermal comfort, heat islands, and land-use changes. He pioneered global-scale urban observation via the Group on Earth Observation (GEO) initiative and developed frameworks integrating geospatial technology with climate resilience strategies. Recent publications highlight advancements in GeoAI for urban thermal stress assessment, road extraction algorithms, and multi-temporal data fusion techniques. His work spans interdisciplinary domains, connecting remote sensing, urban science, and sustainability metrics across diverse climate zones. NASA Senior Fellowship (2008) Taylor & Francis Lifetime Achievements Award (2019) AAG Wilbanks Prize (2024) Lifetime Achievement in Remote Sensing Award (2024) Academia Europaea Foreign Member (2021) As Editor-in-Chief of the ISPRS Journal, Professor Weng has advanced global remote sensing discourse. His research has been supported by NSF, NASA, USAID, Microsoft, and Hong Kong Research Grant Council. He has delivered over 130 invited talks and established visiting professorships in Japan, France, and China.
Guofeng Cao is an Associate Professor in the Department of Geography at the University of Colorado . His research integrates GIScience , GeoAI , geostatistics , and remote sensing to develop advanced methodologies for analyzing heterogeneous geospatial data and modeling complex spatiotemporal patterns. Focus areas: Uncertainty-aware geographic knowledge discovery, land cover/land use dynamics, spatiotemporal bias analysis, geospatial cyberinfrastructure development Applications: Natural hazards, environmental science, public health, global change studies Recent publications emphasize generative adversarial networks for climate downscaling, neural processes for uncertainty modeling, and fusion transformers for disaster assessment. His work combines deep learning with Bayesian inference to address scalability challenges in geospatial data processing. Scientific Recognition : NASA and USDA grants for spatiotemporal research Advising : Mentoring graduate students in geospatial data science Laboratory : Leads the STAR lab (Spatiotemporal Pattern Analysis & Research)
Thierry Badard is an Associate Professor at the Department of Geomatics Sciences , Université Laval, where he also serves as Director of the Center for Research in Geospatial Data and Intelligence (CRDIG) . With over 28 years of experience in geospatial science, he leads research initiatives at the intersection of GeoAI , LiDAR processing , and smart city technologies . Director, CRDIG (2016-2022) Steering Committee Member, Big Data Research Centre (CRDM) Researcher, Institute for Intelligence and Data (IID) Research Expertise spans geospatial big data, GeoNLP, and IoT applications for digital twins. His work addresses flood risk modeling , 3D urban analytics , and environmental monitoring through AI-driven solutions. Recent publications focus on contrastive learning for LiDAR segmentation and geospatial ontologies for early warning systems. Grant Leadership includes collaborative projects on smart insurance analytics (2018-2025), Arctic bioaerosol research (2019-2025), and Quebec-Morocco digital twin partnerships (2022-2023). He has advised 15+ graduate students in geomatics and related fields.
Dr. Kaiqun Fu is an Assistant Professor in the McComish Department of Electrical Engineering and Computer Science at South Dakota State University (SDSU). He holds a Ph.D. and M.S. in Computer Science from Virginia Tech (2021 and 2016). His research focuses on spatial data mining, spatiotemporal event analysis, graph neural networks, and urban computing applications such as traffic impact prediction and social media-driven insights. He also explores physics-informed machine learning for power systems and interdisciplinary topics like 'deaths of despair' in rural areas. Education: Ph.D. in Computer Science, Virginia Tech, 2021 M.S. in Computer Science, Virginia Tech, 2016 Research Interests: His work emphasizes machine learning and deep learning applications in spatial-temporal domains, including: Graph neural networks for traffic incident prediction Social media analysis for urban challenges Physics-informed models for power grid stability Citation forecasting in scientific publications Grants & Projects: NSF CRII ($174,734): Spatiotemporal impacts of traffic events via graph neural networks (2024–2026) NSF EAGER ($300,000): Socio-economic impacts of emerging technologies (2024–2026) SDSU RSCA ($10,118): Graph transformer-based location learning (2023–2024) Professional Involvement: He chairs ACM SIGSPATIAL's SRC committee, serves on SDSU's Computer Science curriculum committees, and is an IEEE member. He co-edits Frontiers in Big Data and advises on interdisciplinary projects like climate-impacted grid security (NSF RII Track-2, $750,000). Labs/Teams: Collaborates with interdisciplinary groups focusing on smart cities, data-driven infrastructure resilience, and GeoAI applications.
Deepak R Mishra is the Merle C. Prunty, Jr. Professor of Geography at the University of Georgia, where he serves as Professor and Head of the Department of Geography. He directs both the Center for Geospatial Research (CGR) and the UGA Small Satellite Research Laboratory (SSRL), demonstrating leadership across multiple significant research initiatives. His academic career spans geospatial science, remote sensing applications, and environmental monitoring with particular focus on coastal ecosystems. Dr. Mishra earned his PhD in Natural Resources from the University of Nebraska, Lincoln in 2006 and completed his M. Tech in Civil Engineering at the Indian Institute of Technology, Kanpur in 2002. His research focuses on combining field-based remote sensing with satellite technologies to monitor and study coastal and inland water resources. His work addresses critical environmental challenges including harmful algal blooms, salt marsh conservation, carbon sequestration in tidal wetlands, and sea level rise impacts. Dr. Mishra's research portfolio reveals strong trends in geospatial analytics for environmental monitoring, with increasing integration of artificial intelligence and small satellite technologies. His recent publications show a growing emphasis on climate change impacts on coastal ecosystems, particularly salt marsh vulnerability and carbon sequestration capacity. The work demonstrates innovative applications of remote sensing for tracking cyanobacterial blooms and developing early warning systems through platforms like CyanoTRACKER. Outstanding Service Award, SEDAAG 2019 Creative Research Medal, University of Georgia, 2017 Best Poster Award, TROPMET 2016, India Article ranked #4 in Altmetric Attention Score in Nature Climate Change 2016 Mississippi State University Faculty Research Award (2012) GRI Academic Faculty of the year (2011) Dr. Mishra has secured substantial research funding, including a $7.5 million NSF LTER grant and a $4.7 million Army Research Lab grant for autonomous navigation systems. His lab actively mentors graduate students including Tyler Lynn, Lishen Mao, and Chintan Maniyar, who contribute to projects spanning coastal monitoring, small satellite development, and AI applications. The Small Satellite Research Laboratory recently achieved a historic milestone with the launch of SPOC satellite to the International Space Station, marking UGA's first satellite deployment.
Wenwen Li is a Professor at Arizona State University (ASU), holding roles as Director of the CyberInfrastructure and Computation Intelligence (CICI) Lab and Research Director at the Spatial Analysis Research Center (SPARC). She specializes in geographic information science, cyberinfrastructure, and geospatial big data. Her work focuses on developing intelligent cyberinfrastructure for environmental and urban studies, leveraging AI and semantic technologies. Li's research has been supported by NSF, USGS, and Google.org, among others. Education: Ph.D. in Earth System and Geoinformation Science (George Mason University, 2010), M.S. in Signal and Information Processing (Chinese Academy of Sciences, 2007), and B.S. in Computer Science (Beijing Normal University, 2004). Research Interests : Cyberinfrastructure, spatial-temporal data mining, semantic interoperability, GeoAI applications in climate science, and urban studies. Her lab, CICI, pioneers projects like the Arctic Permafrost Thaw analysis and disaster response systems. Awards : 2023 AAG and UCGIS Fellowships, 2021 NSF Mid-Career Award, 2015 NSF CAREER Award, and the 2024 Greg Leptoukh Lecture Award (AGU). She chairs AAG's Cyberinfrastructure Specialty Group and serves on editorial boards of key journals. Grants & Service : Leads NSF-funded projects on GeoAI, climate modeling, and Arctic science. Active in AAG leadership roles and global initiatives like the Polar Cyberinfrastructure Portal. Recruits Ph.D. students in Geography and Computer Science. Labs & Teams : Directs the CICI Lab, advancing interdisciplinary GeoAI research and training. Collaborates with global partners on environmental and computational geography projects.
Margaret Kalacska is an Associate Professor in the Department of Geography at McGill University, leading the Applied Remote Sensing Lab. Her research focuses on advancing remote sensing technologies like hyperspectral imaging, Remotely Piloted Aircraft Systems (RPAS), LiDAR, and thermal imaging for environmental science and natural hazard monitoring. She has pioneered the use of RPAS-HSI systems, including developing Canada’s first fully operational RPAS-HSI for the Canadian Airborne Biodiversity Observatory (CABO) since 2018. Dr. Kalacska holds a PhD and MSc in Earth and Atmospheric Sciences from the University of Alberta. Her interdisciplinary work spans Canada, Brazil, Tanzania, Ghana, the Peruvian Amazon, Panama, Madagascar, and Costa Rica. Notable achievements include being the first Canadian woman to lead an airborne hyperspectral mission (MAC-13) in Costa Rica (2013) and receiving the Silver Medal from the Canadian Remote Sensing Society (2018). Her lab specializes in integrating cutting-edge remote sensing tools for biodiversity conservation, ecosystem monitoring, and disaster response. Recent projects include the Fish + Forest initiative studying aquatic habitats in Brazil and advancing custom RPAS for hyperspectral imaging. She also collaborates with the National Research Council of Canada and international organizations like NATO. Awards: Fessenden Prize (2014), Silver Medal (2018), Steacie Prize Nomination (2020) Key Projects: CABO, Fish + Forest , RPAS-HSI System Development Technologies: UAV LiDAR, Structure-from-Motion Photogrammetry, Satellite Data Validation Her research bridges environmental science and technology, emphasizing global applications in conservation and climate resilience.
Monika Kuffer is a Full Professor at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), holding additional roles as Associate Professor in the Department of Urban and Regional Planning and Geo-Information Management. She leads research in urban remote sensing, deprived area monitoring, and sustainable urban development. Her work integrates spatial statistics, machine learning, and citizen science to inform inclusive city planning. Education: PhD in Human Geography & GIS from the University of Twente MSc in Human Geography (TU Munich) MSc in Geographic Information Science (University of London) Research Interests: Urban Remote Sensing Slum and Deprivation Mapping Climate Adaptation Strategies Citizen Science for Urban Inequalities Earth Observation Policy Support Articles Trends: Recent work emphasizes multi-city climate adaptation analyses, thermal inequality assessments in African slums, and scalable deprivation modelling frameworks like IDEAMAPS. Projects like ONEKANA and NightWatch highlight fusion of EO data with community-driven methods. Awards: 2022 EO4all Prize for innovative Earth Observation applications Advising & Grants: Supervised 3 PhD/MSc projects. Active in global initiatives like the EU's Knowledge Centre on EO and the UN's SDG frameworks. Leads datasets on deprivation (e.g., IDeAMapSudan). Labs/Teams: Core member of ITC's Urban Remote Sensing and GeoAI teams. Collaborates with the Digital Society Institute for interdisciplinary urban research.
Di Zhu is an Assistant Professor of Geographic Information Science at the University of Minnesota's Department of Geography, Environment and Society. He directs the Geospatial Data Intelligence (GeoDI) Lab, focusing on GeoAI and social sensing to analyze human-environment interactions in urban systems, public health, and socioeconomic dynamics. His educational background includes a PhD in Cartology and GIScience from Peking University, complemented by a BSc in GIS and a BA in Economics from the same institution. Key research interests include spatial regression models, human mobility patterns, and GeoAI applications. He has collaborated on projects funded by NIH, NSF, and other agencies, exploring topics like spatiotemporal data imputation, urban flow analysis, and pandemic spatial dynamics. His work bridges traditional GIScience with modern machine learning techniques, emphasizing actionable insights from big geospatial data. Teaching focuses on advanced GIS, numerical spatial analysis, and urban sensing. He actively mentors students through the University of Minnesota's Master of GIS program and serves on academic boards including CPGIS. Current projects include analyzing Twin Cities mobility networks and developing intelligent spatial prediction frameworks.
Dr. Judith Verstegen is an Assistant Professor in the Department of Human Geography and Spatial Planning at Utrecht University's Faculty of Geosciences. Her research focuses on geosimulation modeling and spatial optimization, with applications in urban planning, environmental vulnerability assessment, and policy analysis. She leads projects such as HEADS 4 Health (2023-2024), which integrates agent-based models into urban digital twins, and coordinates the GeoSIM research group. Her work emphasizes interdisciplinary collaboration, including projects analyzing linguistic diversity in South America and environmental threats to Amazonian indigenous lands. She is the Program Chair of the MSc Geographical Information Management and Applications (GIMA) program and serves as Editor-in-Chief of the Journal of Spatial Information Science. Notable contributions include methodologies for spatial optimization under uncertainty and agent-based modeling of pedestrian behavior in urban environments. Key research areas include applied data science, complex systems analysis, and the PtS - Transforming Cities initiative. She has advised PhD students on topics ranging from fire prevention optimization to indigenous land vulnerability. Her lab at the University of Münster previously focused on spatial modeling frameworks, and she collaborates internationally with institutions like Leiden University and the PBL Netherlands Environmental Assessment Agency. Recent projects highlight innovation in computational methods, such as Python-based open-source tools for land-use modeling (IMAGE-land) and immersive video experiments for behavioral studies. Her work bridges theoretical modeling with practical policy applications, addressing challenges in sustainable urban development and environmental conservation.
Wenzheng Li is a Visiting Lecturer in the Department of City and Regional Planning at Cornell University’s College of Architecture, Art, and Planning. He earned his Ph.D. in City and Regional Planning from Cornell in August 2024, following a Master’s in Regional Planning from the same institution and a Bachelor’s in Remote Sensing from China University of Geosciences. His research centers on regional-scale land use planning, sustainable urban forms, polycentric development, and environmental sustainability, with applications in Germany, China, and Sub-Saharan Africa. He employs GIS, remote sensing, spatial econometrics, and urban data analytics to investigate urban dynamics and planning policy impacts. His recent publications and conference presentations focus on topics such as the urban heat island effect, polycentric development, and regional equity. These works reveal consistent trends in analyzing spatial configurations for sustainability and equity, particularly through quantitative modeling and cross-national comparisons. C.V. Starr Fellowship, the Einaudi Center of Cornell University, 2023 Li teaches courses in GIS, urban data science, and quantitative methods, emphasizing the integration of machine learning and GeoAI with planning theory. His professional experience includes work on equitable transportation solutions in Tompkins County. He has not advised any students yet, and no grant details beyond the fellowship are mentioned. He is actively involved in research projects on sustainable urban forms in Sub-Saharan Africa, regional governance in China and the U.S., and environmental amenity valuation, reflecting a strong interdisciplinary and global approach to urban and regional planning challenges.
