Integrating Artificial Intelligence and Geospatial Intelligence: Innovative Methods and Applications in Human Mobility Modeling

Tuesday, 18 November 2025 (UTC+10)

Star, Broadbeach, Gold Coast, Australia | Room: Currumbin

Location & Virtual Participation

Venue

Star, Broadbeach

Gold Coast, Australia

Room: Currumbin

Join via Zoom

Meeting ID: 972 7181 7376

Passcode: 262836

Workshop Scope & Topics

This half-day workshop aims to bring together researchers and practitioners to advance the modeling, mining, and simulation of human mobility for intelligent transportation systems and urban analytics. As the Internet of Things and smart city infrastructure produce massive, multi-modal mobility datasets, there is both an opportunity and a responsibility: to build scalable, transferable, and privacy-aware models that capture the dynamics of human movement across time, space, and social interaction.

We will explore AI-empowered and data-driven methods for modeling human mobility and travel behavior, focusing on how mobility behaviors influence and be influenced by transportation systems. This workshop will examine techniques spanning different levels of resolution—from coarse-grained trip and flow modeling to fine-grained activity chains, trajectories, and agent interactions—supporting diverse applications in planning and operations, such as demand forecasting, policy evaluation, infrastructure planning, anomaly detection, and traffic simulation.

This workshop connects the AI, transportation, and geospatial communities to accelerate the development of actionable tools for understanding and simulating human mobility at scale. It invites contributions that address the challenges and opportunities in data fusion, behavioral modeling, real-time analytics, and system-level decision support.

Topics of interest include, but are not limited to:

  • Mobility pattern recognition and travel behavior modeling
  • Cross-domain multi-modal mobility data fusion
  • Scalable mobility data mining and enrichment
  • Modeling and synthesizing normal and atypical mobility
  • Transportation-focused applications of human mobility modeling, including simulation, policy evaluation, and system optimization
  • LLMs and foundation models for mobility analysis

Keynote Speakers

We are pleased to announce four distinguished keynote speakers who are leading experts in AI, geospatial intelligence, and human mobility modeling. Their presentations will provide insights into the latest research developments and future directions in these rapidly evolving fields.

Dr. Meead Saberi

Dr. Meead Saberi

Associate Professor

University of New South Wales

Dr. Meead Saberi is an Associate Professor in the School of Civil and Environmental Engineering at the University of New South Wales (UNSW), Sydney, Australia. He holds a PhD in Transportation Systems Analysis and Planning from Northwestern University. His research focuses on transportation network modeling and the use of emerging data sources to understand network-level mobility patterns, with a particular emphasis on active and sustainable transport.

Dr. Khurram Shafique

Dr. Khurram Shafique

President

Novateur Research Solutions

Dr. Khurram Shafique is a leading expert in artificial intelligence, computer vision, and geospatial analytics, with over 25 years of experience at the intersection of applied research and operational technology development. He serves as the President of Novateur Research Solutions, where he leads the design and deployment of AI-enabled systems for large-scale, data-intensive applications in geospatial intelligence, mobility analysis, and complex sensor environments.

Dr. Shafique has led numerous research and development programs addressing complex challenges in machine learning, sensor data analysis, automated pattern recognition, and large-scale geospatial modeling. His work has involved leading multidisciplinary teams in the development of adaptive, context-aware technologies designed to process and interpret multimodal spatiotemporal data at scale.

Dr. Shafique's work has been published in leading journals and conferences spanning machine learning, computer vision, geospatial intelligence, and applied mathematics. His work has received multiple recognitions, including the Best Student Paper Award at IEEE MDM 2025, the Best Vision Paper Award at ACM SIGSPATIAL 2023, and an IBM Best Paper Award nomination at the ACM Multimedia Conference. A sustained focus of his research is anomaly detection in human mobility, particularly the development of techniques for identifying deviations in large-scale geospatial datasets. He is also a Founding Chair of the GeoAnomalies Workshop, organized in conjunction with ACM SIGSPATIAL.

Dr. Shafique earned his Ph.D. in Computer Science from the University of Central Florida in 2004.

Dr. Yaoyi Chiang

Dr. Yaoyi Chiang

Associate Professor

University of Minnesota

Dr. Yao-Yi Chiang is an Associate Professor in the Department of Computer Science & Engineering at the University of Minnesota. Dr. Chiang's research interests are in spatial artificial intelligence. His work focuses on developing innovative AI methods to decode the complex interplay between environmental systems and human activity—often using sparse, uneven, and multi-scale spatiotemporal data. Dr. Chiang's research has received support from leading federal agencies such as NSF, NEH, NIH, DARPA, IARPA, and NGA, as well as industry leaders including NTT Global Networks and BAE Systems. He has served as a visiting researcher at Google AI, a machine learning consultant at Meta, and the Chief Scientist at AirMap, a pioneer in drone airspace management. Dr. Chiang founded the Kartta Foundation, a nonprofit organization dedicated to assembling and refining geographic data for the public good. The foundation now manages Kartta Labs, originally launched at Google.

Dr. Ryan Qi Wang

Dr. Ryan Qi Wang

Associate Professor

Northeastern University

Dr. Ryan Qi Wang is an Associate Professor and Vice Chair for Research in the Department of Civil and Environmental Engineering at Northeastern University. Before joining Northeastern, Wang was a postdoc fellow at the Department of Sociology, Harvard University. He received his Ph.D. degree from the Department of Civil and Environmental Engineering at Virginia Tech. His research focuses on two interrelated areas: human movement perturbation under the influence of natural and manmade disasters, and mobility equality in big cities.

His research has been published in Nature Computational Science, Nature Human Behavior, Proceedings of National Academy of Sciences (PNAS), etc. His research group has received funding support from NSF, NIST, IARPA, MacArthur Foundation, USDOT, and other foundations and local government agencies.

Lightning Talk Speakers

We are excited to feature lightning talks from emerging researchers who are pushing the boundaries of human mobility modeling and AI applications in transportation.

Shihao Gong

Shihao Gong

Master's Student

Tongji University

Shi-Hao Gong is a master's student in Urban Mobility at Tongji University, advised by Professor Jing Teng. His research interests mainly include spatiotemporal data mining and travel behavior analysis. His research have been published in journals such as Research in Transportation Business & Management and Railway Transport and Economy.

Mingyue Li

Mingyue Li

Master's Student

Tongji University

Mingyue Li is currently a master student in Transportation Engineering at Tongji University. Her research interests focus on the application of AI and geospatial intelligence to urban mobility forecasting, human mobility analysis cross mega-cities, and the optimization of urban transportation systems.

Yiping Liu

Yiping Liu

Ph.D. Student

KAIST Cho Chun Shik Graduate School of Mobility

Yiping Liu obtained his Bachelor's degree from Chongqing University and his Master's degree from Southeast University. He is currently pursuing a Ph.D. at the KAIST Cho Chun Shik Graduate School of Mobility. His research focuses on traffic safety modeling, travel behavior analysis, and the application of large language models (LLMs) in generating and recommending personalized mobility solutions.

Workshop Schedule

Half-day workshop schedule (all times in UTC+10)

Time Activity Speaker Title
13:30 – 13:40 Welcome and Introduction Professor Jiaqi Ma
13:40 – 14:20 Talk 1 Professor Yaoyi Chiang Bridging Language and Geography: Encoding Foundation Data for Human Mobility Mining
14:20 – 15:00 Talk 2 Professor Qi Wang From Global Plans to Local Action: Unifying LLMs and Diffusion for Urban Mobility
15:00 – 15:10 Lightning Talk 1 Shihao Gong, Tongji Improving Multi-Modal Transportation Recommendation Systems through Spatio-Temporal Semantic Embedding
15:10 – 15:30 Break (20 min)
15:30 – 16:10 Talk 3 Professor Meead Saberi Active Mobility Modeling: From Classical Approaches to AI-Driven Methods
16:10 – 16:50 Talk 4 Dr. Khurram Shafique Through the looking glass of human mobility: Anomalies that open doors to new models, maps, and policies.
16:50 – 17:00 Lightning Talk 2 Professor Jiaqi Ma TBD
17:00 – 17:10 Break (10 min)
17:10 – 17:20 Lightning Talk 3 Mingyue Li, Tongji A Hybrid Attention-Enhanced Spatio-Temporal Graph Network for Continuous-Time Multi-Task Urban Human Mobility Forecasting
17:20 – 17:30 Lightning Talk 4 Yiping Liu, KAIST LLM-TripPlanner: A Large-Language-Model-Based Agent for Personalized Trip Planning

Organizing Committee

The workshop is organized by a distinguished committee of researchers with expertise spanning artificial intelligence, geospatial intelligence, and human mobility modeling.

Xishun Liao

Xishun Liao

Assistant Professor

University of Central Florida

Yifan Liu

Yifan Liu

Ph.D. Student

University of California, Los Angeles

Haoxuan Ma

Haoxuan Ma

Ph.D. Student

University of California, Los Angeles

Yuan Liao

Yuan Liao

Postdoctoral Research Fellow

Chalmers University of Technology

Shangqing Cao

Shangqing Cao

Ph.D. Student

University of California, Berkeley

Yueshuai He

Yueshuai He

Assistant Professor

University of Louisville

Marta Gonzalez

Marta Gonzalez

Associate Professor

University of California, Berkeley

Xu Han

Xu Han

Ph.D. Student

University of California, Los Angeles

Jiaqi Ma

Jiaqi Ma

Professor

University of California, Los Angeles

Sponsors

We gratefully acknowledge the support of our sponsors who make this workshop possible.