Sessions
Day 1 - Wednesday, October 30
Session 1: LLM and Mobility (8:00 - 9:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
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Urban Mobility Assessment Using LLMs (Paper)
Prabin Bhandari: Department of Computer Science, George Mason University
Antonios Anastasopoulos: Department of Computer Science, George Mason University
Dieter Pfoser: Department of Geography and Geoinformation Science, George Mason University -
Prompt Mining for Language Models-based Mobility Flow Forecasting (Paper)
Hao Xue: University of New South Wales
Tianye Tang: University of New South Wales
Ali Payani: Cisco Research
Flora D. Salim: University of New South Wales -
Harnessing LLMs for Cross-City OD Flow Prediction (Paper)
Chenyang Yu: University of North Texas
Xinpeng Xie: University of North Texas
Yan Huang: University of North Texas
Chenxi Qiu: Department of Computer Science and Engineering, University of North Texas
Session 2: Computational Geometry and Spatial Graph Processing (10:30 - 12:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
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Critical Features Tracking on Triangulated Irregular Networks by a Scale-Space Method (Paper)
Haoan Feng: University of Maryland
Yunting Song: University of Maryland
Leila De Floriani: University of Maryland -
Revisiting the Bus Stop Problem in Road Networks (Paper)
Claudius Proissl: University of Stuttgart
Daniel Koch: University of Stuttgart -
Discretized Random Walk Models for Efficient Movement Interpolation (Paper)
Kevin Buchin: Department of Computer Science, Technical University Dortmund
Mart Hagedoorn: Department of Computer Science, Technical University Dortmund
Alexander Korn: University of Cologne -
A Framework for Automated Junction Monitoring (Paper)
Rodrigo Sasse David: Aalborg University
Kristian Torp: Aalborg University
Mahmoud Sakr: Universite Libre de Bruxelles
Esteban Zimanyi: Universite Libre de Bruxelles -
Calculating Upstream Relation in Spatial Networks Under Path Constraints (Paper)
Wejdene Mansour: Professorship of Big Geospatial Data Management, Technical University of Munich
Martin Werner: Professorship of Big Geospatial Data Management, Technical University of Munich
Session 3: Spatio-Temporal Learning on Graphs (13:00 - 14:30)
Session Chair: TBD
Room: TBD
Paper Type: Research
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Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning (Paper)
Junfeng Hu: National University of Singapore
Xu Liu: National University of Singapore
Zhencheng Fan: University of Technology Sydney
Yuxuan Liang: The Hong Kong University of Science and Technology (Guangzhou)
Roger Zimmermann: National University of Singapore -
Enhancing Dependency Dynamics in Traffic Flow Forecasting via Graph Risk Bootstrap (Paper)
Qiang Gao: Southwestern University of Finance and Economics
Zizheng Wang: Southwestern University of Finance and Economics
Li Huang: Southwestern University of Finance and Economics
Goce Trajcevski: Iowa State University
Kunpeng Zhang: University of Maryland
Xueqin Chen: Delft University of Technology -
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks (Paper)
Dingyi Zhuang: Massachusetts Institute of Technology
Yuheng Bu: University of Florida
Guang Wang: Florida State University
Shenhao Wang: University of Florida
Jinhua Zhao: Massachusetts Institute of Technology -
Enhancing Graph Neural Networks in Large-scale Traffic Incident Analysis with Concurrency Hypothesis (Paper)
Xiwen Chen: Clemson University
Sayed Pedram Haeri Boroujeni: Clemson University
Xin Shu: Northeastern University
Huayu Li: University of Arizona
Abolfazl Razi: Clemson University -
Regional Features Conditioned Diffusion Models for 5G Network Traffic Generation (Paper)
Xiaoqian Qi: Department of Electronic Engineering, BNRist, Tsinghua University
Haoye Chai: Department of Electronic Engineering, BNRist, Tsinghua University
Li Yu: China Mobile Research Institute
Yong Li: Department of Electronic Engineering, BNRist, Tsinghua University
Zhaocheng Wang: Department of Electronic Engineering, BNRist, Tsinghua University
Data & Resources Track (16:00 - 16:30)
Session Chair: TBD
Room: TBD
Paper Type: Data and Resources Track
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CC-GPX: Extracting High-Quality Annotated Geospatial Data from Common Crawl (Paper)
Ilya Ilyankou: SpaceTimeLab, University College London
Meihui Wang: SpaceTimeLab, University College London
Stefano Cavazzi: Ordnance Survey
James Haworth: SpaceTimeLab, University College London -
Dockless Electric Scooters Worldwide: Methods and Analysis (Paper)
Hassan Ali Khan: Computer Science, North Carolina State University
Muhammad Shahzad: Computer Science, North Carolina State University
Guoliang Jin: Computer Science, North Carolina State University -
GUI: A Comprehensive Dataset of Global Urban Infrastructure Based on Geospatial Visual Foundation Models (Paper)
Zhenyu Han: Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist)
Xin Zhang: Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist)
Yanxin Xi: University of Helsinki
Yan Luo: Media Lab, Massachusetts Institute of Technology
Tong Xia: Department of Computer Science and Technology, University of Cambridge
Yong Li: Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist) -
Data and Resources for Combining Point of Interest Semantics, Locations, and Road Networks (Paper)
Joseph Zuber: Iowa State University
Xu Teng: ESRI
Andreas Zufle: Emory University
Goce Trajcevski: Iowa State University
Day 2 - Thursday, October 31
Session 4: Remote Sensing and Climate Science (8:00 - 9:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
-
Multilingual Vision-Language Pre-training for the Remote Sensing Domain (Paper)
Joao Daniel Silva: IST and INESC-ID - Instituto Superior Tecnico, University of Lisbon
Joao Magalhaes: Universidade NOVA de Lisboa
Devis Tuia: Ecole Polytechnique Federale de Lausanne
Bruno Martins: IST and INESC-ID - Instituto Superior Tecnico, University of Lisbon -
DeepSoil: A Science-guided Framework for Generating High Precision Soil Moisture Maps by Reconciling Measurement Profiles Across In-situ and Remote Sensing Data (Paper)
Paahuni Khandelwal: Department of Computer Science, Colorado State University
Sangmi Lee Pallickara: Department of Computer Science, Colorado State University
Shrideep Pallickara: Department of Computer Science, Colorado State University -
Towards Kriging-informed Conditional Diffusion for Regional Sea-Level Data Downscaling: A Summary of Results (Paper)
Subhankar Ghosh: Computer Science, University of Minnesota, Twin Cities
Arun Sharma: Computer Science, University of Minnesota, Twin Cities
Jayant Gupta: Oracle Inc., USA
Aneesh Subramanian: Atmospheric Sciences, University of Colorado, Boulder
Shashi Shekhar: Computer Science, University of Minnesota, Twin Cities
Vision Track (10:30 - 12:00)
Session Chair: TBD
Room: TBD
Paper Type: Vision
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SRL: Towards a General-Purpose Framework for Spatial Representation Learning (Paper)
Gengchen Mai: Geography and the Environment, University of Texas at Austin
Xiaobai Yao: Geography, University of Georgia
Yiqun Xie: Geographical Sciences, University of Maryland, College Park
Jinmeng Rao: Google DeepMind
Hao Li: Techinical Universtiy of Munich
Qing Zhu: Lawrence Berkeley National Lab
Ziyuan Li: University of Connecticut
Ni Lao: Google LLC -
Beyond the Commute: Unlocking the Potential of Electric Vehicles as Future Energy Storage Solutions (Vision Paper) (Paper)
Muhammad Aamir Cheema: Monash University
Hao Wang: Monash University, Australia
Wei Wang: Hong Kong University of Science and Technology (Guangzhou), China
Adel Nadjaran Toosi: The University of Melbourne, Australia
Egemen Tanin: The University of Melbourne, Australia
Jianzhong Qi: The University of Melbourne, Australia
Hanan Samet: University of Maryland -
Vision: Leveraging Low Earth Orbit Satellites for Future Ubiquitous Positioning (Paper)
Sherif Mostafa: The American University in Cairo
Mahmoud Elsanhoury: University of Vaasa
Jaakko Yliaho: University of Vaasa
Janne Koljonen: University of Vaasa
Heidi Kuusniemi: University of Vaasa
Mohammed Elmusrati: University of Vaasa
Khaled A. Harras: Carnegie Mellon University
Moustafa Youssef: The American University in Cairo -
A Geospatial Perspective on Data Ownerships, the Right to be Forgotten, Copyrights, and Plagiarism in Generative AI (Paper)
Yaron Kanza: AT&T Labs - Research
Balachander Krishnamurthy: AT&T Labs-Research
Divesh Srivastava: AT&T Labs-Research -
A roadmap for generative mapping ? unlocking the power of generative AI for map-making (Paper)
Sidi Wu: ETH Zurich
Katharina Henggeler: ETH Zurich
Yizi Chen: ETH Zurich
Lorenz Hurni: ETH Zurich
Session 5: Mobility Mining (13:00 - 14:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
-
Trajectory Anomaly Detection with Language Models (Paper)
Jonathan Mbuya: George Mason University
Dieter Pfoser: George Mason University
Antonios Anastasopoulos: George Mason University -
Beauty or Beast: Human Behavioral Insights and Learning Power of Federated Mobility Prediction (Paper)
João Paulo Esper: Universidade Federal de Minas Gerais
Aline Carneiro Viana: Inria
Jussara Almeida: Universidade Federal de Minas Gerais -
Transferable Unsupervised Outlier Detection Framework for Human Semantic Trajectories (Paper)
Zheng Zhang: Emory University
Hossein Amiri: Emory University
Dazhou Yu: Emory University
Yuntong Hu: Emory University
Liang Zhao: Emory University
Andreas Zufle: Emory University
Day 3 - Friday, November 1
Session 6: Prediction and forecasting (8:00 - 9:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
-
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned (Paper)
Du Yin: School of Computer Science and Engineering of UNSW
Jinliang Deng: HKGAI, Hong Kong SAR
Southern University of Science and Technology, China
Shuang Ao: School of Computer Science and Engineering of UNSW
Zechen Li: School of Computer Science and Engineering of UNSW
Hao Xue: School of Computer Science and Engineering of UNSW
Arian Prabowo: School of Computer Science and Engineering of UNSW
Renhe Jiang: Center for Spatial Information Science, The University of Tokyo
Xuan Song: School of Artificial Intelligence of Jilin University, Southern University of Science and Technology
Flora Salim: School of Computer Science and Engineering of UNSW -
CMAD: Advancing Understanding of Geospatial Clusters of Anomalous Melt Events in Sea Ice Extent (Paper)
Maloy Kumar Devnath: Information Systems, University of Maryland, Baltimore County
Sudip Chakraborty: Information Systems, University of Maryland, Baltimore County
Vandana P. Janeja: Information Systems, University of Maryland, Baltimore County -
GraphParcelNet: Predicting Parcel-Level Imperviousness from Geospatial Vector Data using Graph Neural Networks (Paper)
Lapone Techapinyawat: Texas A&M University-Corpus Christi
Wenlu Wang: Texas A&M University-Corpus Christi
Mehrube Mehrubeoglu: Texas A&M University-Corpus Christi
Hua Zhang: Texas A&M University-Corpus Christi
Industry & Systems Track (10:30 - 12:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
-
Adaptive Dispatching of Mobile Charging Stations using Multi-Agent Graph Convolutional Cooperative-Competitive Reinforcement Learning (Paper)
Shimon Wonsak: Volkswagen AG
Nils Henke: Volkswagen AG
Mohammad Al-Rifai: Volkswagen AG
Michael Nolting: Volkswagen AG
Wolfgang Nejdl: L3S Research Center -
Multi-Entry Generalized Search Trees for Indexing Trajectories (Paper)
Maxime Schoemans: Université libre de Bruxelles
Walid G. Aref: Purdue University
Esteban Zimányi: Université libre de Bruxelles
Mahmoud Sakr: Université libre de Bruxelles -
Learning to Estimate Package Delivery Time in Mixed Imbalanced Delivery and Pickup Logistics Services (Paper)
Jinhui Yi: Tsinghua University
Huan Yan: Tsinghua University
Haotian Wang: Rutgers University
Jian Yuan: Tsinghua University
Yong Li: Tsinghua University -
Mapping Passenger Trajectories to Train Schedules - industrial paper (Paper)
Lorenzo Padoan: Department of Information Engineering, University of Padova,Motion Analytica s.r.l.
Francesco Silvestri: Department of Information Engineering, University of Padova
Bruno Zamengo: Motion Analytica s.r.l. -
Accurate Customer Address Matching via Weak Supervision for Geocode Learning (Paper)
Arpan Paul: Amazon
Saket Maheshwary: Amazon
Saurabh Sohoney: Amazon
Session 7: Urban Computing and Human Mobility (13:00 - 14:30)
Session Chair: TBD
Room: TBD
Paper Type: Research
-
EFECTIW-ROTER: Deep Reinforcement Learning Approach for Solving Heterogeneous Fleet and Demand Vehicle Routing Problem With Time-Window Constraints (Paper)
Arash Mozhdehi: Department of Geomatics Engineering, University of Calgary
Mahdi Mohammadizadeh: Department of Geomatics Engineering, University of Calgary
Yunli Wang: National Research Council
Sun Sun: National Research Council
Xin Wang: Department of Geomatics Engineering, University of Calgary -
Deep Reinforcement Learning for Multi-Period Facility Location: pk-median Dynamic Location Problem (Paper)
Changhao Miao: Beijing Institute of Technology
Yuntian Zhang: Beijing Institute of Technology
Tongyu Wu: Beijing Institute of Technology
Fang Deng: Beijing Institute of Technology
Chen Chen: Beijing Institute of Technology -
ModeSense: Ubiquitous and Accurate Transportation Mode Detection using Serving Cell Tower Information (Paper)
Sherif Mostafa: The American University in Cairo
Moustafa Youssef: The American University in Cairo
Khaled A. Harras: Carnegie Mellon University -
M3LUC: Multi-modal Model for Urban Land-Use Classification (Paper)
Sibo Li: Department of Electronic Engineering, BNRist, Tsinghua University
Xin Zhang: Shenzhen International Graduate School, Tsinghua University
Yuming Lin: Department of Electronic Engineering, BNRist, Tsinghua University
Yong Li: Department of Electronic Engineering, BNRist, Tsinghua University -
SARN: Structurally-Aware Recurrent Network for Spatio-Temporal Disaggregation (Paper)
Bin Han: University of Washington
Bill Howe: University of Washington
Session 8: Privacy and Security (15:00 - 16:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
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Protecting Vehicle Location Privacy with Contextually-Driven Synthetic Location Generation (Paper)
Sourabh Yadav: Department of Computer Science and Engineering, University of North Texas
Chenyang Yu: Department of Computer Science and Engineering, University of North Texas
Xinpeng Xie: Department of Computer Science and Engineering, University of North Texas
Yan Huang: Department of Computer Science and Engineering, University of North Texas
Chenxi Qiu: Department of Computer Science and Engineering, University of North Texas -
Privacy preserved taxi demand prediction system for distributed data (Paper)
Ren Ozeki: Osaka University
Haruki Yonekura: Osaka University
Hamada Rizk: Osaka University
Hirozumi Yamaguchi: Osaka University -
Adversarial Reconstruction of Trajectories: Privacy Risks and Attack Models in Trajectory Embedding (Paper)
Haochen Han: Shanghai Jiao Tong University
Shuaiyu Yang: Shanghai Jiao Tong University
Jiaxin Ding: Shanghai Jiao Tong University
Luoyi Fu: Shanghai Jiao Tong University
Xinbing Wang: Shanghai Jiao Tong University
Chenghu Zhou: Chinese Academy of Sciences
Session 9: Spatial Data Generation and Augmentation (16:00 - 17:00)
Session Chair: TBD
Room: TBD
Paper Type: Research
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Augmentation Techniques for Balancing Spatial Datasets in Machine and Deep Learning Applications (Paper)
Alberto Belussi: Department of Computer Science, University of Verona
Diego Garofolo: Department of Computer Science, University of Verona
Sara Migliorini: Department of Computer Science, University of Verona -
WildGraph: Realistic Long-Horizon Trajectory Generation with Limited Sample Size (Paper)
Ali Al-Lawati: The Pennsylvania State University
Elsayed Eshra: The Pennsylvania State University
Prasenjit Mitra: The Pennsylvania State University -
TrajGPT: Controlled Synthetic Trajectory Generation Using a Multitask Transformer-Based Spatiotemporal Model (Paper)
Shang-Ling Hsu: University of Southern California
Emmanuel Tung: Novateur Research Solutions
John Krumm: University of Southern California
Cyrus Shahabi: University of Southern California
Khurram Shafique: Novateur Research Solutions
