The 2026 Summer School on Spatiotemporal AI
August 4-6, 2026
Virginia Tech Academic Building One, 3625 Potomac Avenue, Alexandria, VA 22305
Sponsored by the NSF Spatiotemporal Innovation Center and Virginia Tech, the 2026 Summer School on Spatiotemporal AI offers an intensive, hands-on introduction to the latest advances in spatiotemporal AI, including GeoAI (Geospatial Artificial Intelligence), Generative AI, and Autonomous GIS.
Participants will explore cutting-edge AI-driven geospatial analytics, automation, and predictive modeling through replicable and scalable methods for analyzing complex spatiotemporal datasets for insights. The program highlights how these technologies are transforming decision-making in key domains, including Public Health, Business & Market Analytics, Human Mobility, Remote Sensing & Earth Observation, and Environmental Management.
Attendees will collaborate with leading scientists and industry experts while gaining practical skills in AI-powered spatiotemporal data science.
Core topics: (1) foundations of spatiotemporal AI; (2) advances in cloud computing for spatiotemporal AI; (3) integration of GeoAI and generative AI in research design, spatial modeling, and applications; (4) autonomous GIS; and (5) future trends of spatiotemporal AI.
Tools and Technologies Covered: cloud platforms for spatiotemporal AI, Python-based environments (Google Colab, Jupyter Notebooks), geospatial libraries (GeoPandas, Rasterio), AI-assisted tools (ChatGPT, Gemini and Google Scholar), autonomous spatial analysis, GIS agent development, and applied GeoAI workflows for satellite image analysis, mapping, and spatial intelligence.
Tentative Agenda (3 days)
Day One:
- Foundations of Spatiotemporal AI
1-1: Foundations of GeoAI and Intelligent Systems (35-40 for each presentation)
(Core concepts, theory, and paradigms shaping spatiotemporal AI)
- The Foundation AI Disruption to Research and Education
- GeoAI: The New Frontier
- GeoAI: Turning Data into Public Health Impact
- GeoAI and Smart Disaster Mitigation
1-2: Hands-on Practice: AI-Assisted Analysis with Python in Google Colab
- Cloud Computing with Python in Google Colab
- AI Copilot for Geospatial Data Analysis
- Data Mapping with GeoPandas
- Satellite Image Analysis with Rasterio
- Case Study: Urban Poverty and Healthcare Access
Day Two:
- Advances in Spatiotemporal AI: Human-Centered AI Analytics and Decisions
2-1: Advances in Spatiotemporal AI: Autonomous GIS and Generative AI for Analytics and Decisions (35-40 min for each presentation and demo/hands-on practice)
(Understanding, governing, collaborating, and decision with AI systems)
- Foundations of Autonomous GIS and Agentic Geospatial Systems
- Human-AI Collaboration in Autonomous Spatial Analysis, Modeling, and Research
- Research Architect: A Human-in-the-Loop Research Architecture
- Demos and Hands-on Practices
2-2: Hands-on Practice: Generative AI Tools for Research and Writing
- Using ChatGPT as an Assistant for Writing
- Leveraging Google Scholar and Gemini/ChatGPT for Literature Review
- AI Assisted Research Design
- Case Study: Wildfire Research
Day Three:
III. Spatiotemporal AI Applications and Future Trends
3-1: Applications and Societal Impact (30 min for each presentation)
(Real-world deployment across domains and challenges)
- GeoAI for Regional Conflicts
- From Decision Trees to Deep Learning
- GeoAI Applications for Transportation Environments and User Experience Auditing
- Generative AI workforce and Job Market
- GeoAI for Healthcare Analytics
- GeoAI for Historical Map Information Extraction
- GeoAI for Urban Representations
- Generative AI for Smart Urban Management
3-2: Panel Discussion: Future Trends of Spatiotemporal AI
- Disruption, Adaptation, and Response for AI in Research and Education
- Open Discussion
Requirements:
A background in geographic analysis or related fields is desirable. All participants are expected to actively engage in class assignments and group and discussions. Participants who successfully complete the program will receive a certificate of completion. Outstanding participants will be invited to join the research team of the Spatiotemporal Innovation Center project.
Application:
Please submit your application via the following form: https://forms.gle/2HMnUUymHxc3eK4w7 before May 30, 2026. Application will be open until all seats are filled.
Detailed agenda and lodging information will be provided to accepted participants. Participants are responsible for their own travel and accommodation expenses.
For more information, please visit https://stds.stcenter.net or contact: 2026-stc-conference@googlegroups.com.
Registration Fee:
- $1,980 registered/paid before 0:00 am ET, June 30, 2026
- $2,680 registered/paid after 0:00 am ET, June 30, 2026
Lecturers:
- Chaowei Yang, George Mason University
- Siqin Wang, University of Southern California
- Xiao Huang, Emory University
- Qunying Huang, University of Wisconsin
- Zhenlong Li, The Pennsylvania State University
- Manzhu Yu, The Pennsylvania State University
- Zifu Wang, Harvard University
- Lingbo Liu, Harvard University
- Armita Kar, George Mason University
- Shanjiang Zhu, George Mason University
- Mengxi Zhang, Virginia Tech
- Junghwan Kim, Virginia Tech
Instructors:
- Anusha Srirenganathanmalarvizhi George Mason University
- Andrew Yang, Northeastern University
- Temitope Akinboyewa, The Pennsylvania State University
- Yahya Masri, George Mason University
- Ning Huan, Emory University
- Seren Smith, George Mason University
- Qifan Wu, Emory University
- Shoibolina Kaushik, Emory University
- Yuhao Jia, Emory University
Location:
The in-person sessions will be held at Virginia Tech Academic Building One, 3625 Potomac Avenue, Alexandria, VA 22305, which is less than 2 miles from the Ronald Reagan Washington National Airport. Online participants will receive a Zoom link prior to the event.
Contact: Please contact office@spatialdatalab.org if there are any questions.
