BEGIN:VCALENDAR
VERSION:2.0
X-WR-CALNAME:ucgissymposium2026
X-WR-CALDESC:Event Calendar
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//Sched.com UCGIS Symposium 2026//EN
X-WR-TIMEZONE:UTC
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260615T123000Z
DTEND:20260615T160000Z
SUMMARY:Advancing Social Media Analytics in Neo4j: Multimodal Embeddings and AI Agents with Knowledge Graphs
DESCRIPTION:Half-day\, hands-on workshop on AI-powered social media analytics using multimodal embeddings and knowledge graphs in Neo4j. Participants will use a curated Twitter/X-style dataset to build AI agents that utilize vector search and graph structures for in-depth analysis. Prior tutorial context: https://github.com/xbwei/data-analysis-with-generative-ai\n\nThis workshop requires registration - click here to register\n\nAbstract\n\nBuilding on the instructor’s earlier workshops on generative AI in social analytics (see: https://github.com/xbwei/data-analysis-with-generative-ai)\, this hands-on session introduces participants to advanced techniques in multimodal embeddings and Agent-Based Knowledge Graphs. While previous versions focused on flat storage (e.g.\, MongoDB)\, this workshop emphasizes the need to model social data as a connected network that AI Agents can use for reasoning and analysis.\n\nTo maximize learning time\, the workshop uses curated\, pre-packaged datasets. This enables participants to bypass API restrictions and focus directly on analytics. Participants will learn how to organize social data into a Neo4j knowledge graph\, representing users\, posts\, and interactions as interconnected nodes instead of isolated documents.\n\nThe core of the workshop examines the intersection of Agentic AI and Network Science. Attendees will create high-dimensional vector embeddings for text and images using modern embedding models and store them directly within graph nodes. This allows the development of Graph-Augmented AI Agents—systems capable of performing semantic vector searches and navigating the graph network to retrieve context. By combining these technologies\, researchers can build agents that synthesize insights from connected nodes\, enabling more nuanced detection of communities and misinformation than traditional methods.\n\nBy the end of the session\, attendees will gain practical skills in:\nGraph Database Foundations: Setting up a Neo4j database and importing social data structures (Nodes & Edges).Multimodal Embeddings: Creating and saving vector embeddings for text and images within the graph to facilitate semantic search.Agent-Based Reasoning: Developing agent workflows that leverage vector retrieval and graph traversal to enable evidence-based analysis.\n\n
CATEGORIES:WORKSHOP
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:b1e261a67d0384cde82e2e729c6ce736
URL:http://ucgissymposium2026.sched.com/event/b1e261a67d0384cde82e2e729c6ce736
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260615T153000Z
DTEND:20260615T170000Z
SUMMARY:Lunch break (on your own)
DESCRIPTION:
CATEGORIES:MEAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:4c7de598b4bc2def65f37bf4b69909e2
URL:http://ucgissymposium2026.sched.com/event/4c7de598b4bc2def65f37bf4b69909e2
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260615T170000Z
DTEND:20260615T203000Z
SUMMARY:From Prompts to Protocols: Governing Agentic AI for Reliable Geospatial Programming
DESCRIPTION:This workshop introduces AgentLoom\, a dual-helix governance framework for reliable agentic AI in geospatial programming. Participants will leverage Persistent Knowledge and Enforceable Behavioral Constraints to stabilize LLM outputs\, ensuring scientifically rigorous and reproducible software development across complex geospatial workflows. \n\nPrerequisite Knowledge & Materials:\n● Intermediate understanding of programming\n● Laptop with a modern web browser\n● Ideally access to an LLM API key (details to obtain these will be provided) We will also provide a free-tier option\n\nThis workshop requires registration - click here to register \n\nAbstract\nThe transition from passive\, chat-based interfaces to autonomous Agentic AI has revealed a critical reliability gap in scientific software production (e.g. application development or programming-based data analysis). While Large Language Models (LLMs) demonstrate remarkable proficiency in generating localized code snippets\, they consistently struggle with the structural requirements of software development. These models frequently fail to maintain architectural coherence across long-context development cycles\, lack the "memory" to preserve scientific constraints across multiple sessions\, and exhibit stochastic variability that undermines the reproducibility of complex geospatial code.\n\nThis workshop introduces a dual-helix governance framework designed to move beyond "prompt engineering" toward executable protocols for reliable agentic AI in geospatial contexts. The framework stabilizes agentic execution by decoupling the LLM’s reasoning capabilities from its volatile internal state through two orthogonal axes: Persistent Knowledge Externalization (auditable domain-specific memory) and Enforceable Behavioral Constraints (machine-executable protocols rather than suggestive instructions). The framework is implemented as an open-source software AgentLoom1 that implements a 3-track architecture (Knowledge\, Behavior\, and Skills). This serves as the structural foundation for building a project-specific Knowledge Graph that functions as a persistent\, version-controlled and auditable repository of domain facts\, architectural protocols\, and validated workflows\, ensuring that the agent’s reasoning remains grounded and scientifically rigorous across extended development and interaction cycles.\n\nParticipants will explore this framework and its open-source implementation that addresses five fundamental LLM limitations:\n1. Long-context Fragmentation: Managing codebases that exceed the effective attention window of modern transformers.\n2. Cross-session Forgetting: Maintaining knowledge over multi-day development cycles.\n3. Output Stochasticity: Standardizing architectural patterns to ensure predictable\, reproducible outputs.\n4. Instruction Following Failure: Enforcing strict protocols (e.g.\, geospatial standards\, or accessibility features).\n5. Adaptation Rigidity: Facilitating the transparent evolution of a domain knowledge graph without the need for expensive model fine-tuning.\n\nLearning Outcomes:\n● Set up AgentLoom’s Knowledge/Behavior/Skills tracks for a geospatial project.\n● Identify common reliability failures in LLM-assisted geospatial coding\n● Externalize key domain knowledge and project rules into auditable\, version-controlled artifacts\n● Apply enforceable protocols (checks/tests/constraints) to make agentic outputs more consistent and scientifically valid
CATEGORIES:WORKSHOP
LOCATION:Room B\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:6cd69848f794aece917cbe514b72dede
URL:http://ucgissymposium2026.sched.com/event/6cd69848f794aece917cbe514b72dede
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260615T173000Z
DTEND:20260615T190000Z
SUMMARY:How AI is Powering the Future of Geospatial
DESCRIPTION:This session introduces the foundations of AI within Esri’s ArcGIS platform. It explores how machine learning\, deep learning\, AI assistants\, and large language models integrate with ArcGIS Pro \, ArcGIS Online and ArcGIS apps. We will clarify key terminology\, examine practical GIS-focused AI workflows\, and distinguish between hype and classroom-ready capabilities. Attendees will see examples such as feature extraction\, predictive modeling\, and automated spatial analysis\, along with guidance on positioning AI concepts within existing GIS curricula. \n\nThis workshop requires registration - click here to register
CATEGORIES:WORKSHOP
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:05832e9e4485017be659a86faafff1fd
URL:http://ucgissymposium2026.sched.com/event/05832e9e4485017be659a86faafff1fd
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T120000Z
DTEND:20260616T130000Z
SUMMARY:Continental Breakfast
DESCRIPTION:
CATEGORIES:MEAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:36b3a2773ee320cd8ce9163e7f0b2f36
URL:http://ucgissymposium2026.sched.com/event/36b3a2773ee320cd8ce9163e7f0b2f36
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T130000Z
DTEND:20260616T133000Z
SUMMARY:Opening Session & Welcome
DESCRIPTION:\n
CATEGORIES:PLENARY
LOCATION:Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:a1306bf6d49c3316b64db44e8e56cc60
URL:http://ucgissymposium2026.sched.com/event/a1306bf6d49c3316b64db44e8e56cc60
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T133000Z
DTEND:20260616T142000Z
SUMMARY:Plenary Session: The future of Spatial Intelligence - The opportunity for Leadership
DESCRIPTION:The future of Spatial Intelligence - The opportunity for Leadership\nIn the not-too-distant future\, every decision - investment\, infrastructure\, climate adaptation\, real estate\, farming\, banking - will start with a live conversation with the Earth. In our field\, we have surely moved from looking at the Earth to asking it questions building on the maturity of geospatial technology and computing\, the explosion of earth observation data\, and the proliferation of AI. In an era of 'AI Everywhere\,' the path to true spatial intelligence requires more than just technological advancement\; it demands a radical shift in how we collaborate.\n\nIn her keynote\, Marge Cole draws on her global experience working with NASA\, OGC and a multitude of startups and innovators over the years. Reflecting on the path towards spatial intelligence\, its impact on innovation\, research\, and business opportunties - underscoring the pivotal need for academia and research to forge more cross-disciplinary\, more collaboration\, more agility\, and more partnerships with industry upfront and throughout the research process\, also examining the unique opportunities and challenges this rapid evolution presents for education and research.
CATEGORIES:PLENARY
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:29f478bfe32ba9420233380c23ff67af
URL:http://ucgissymposium2026.sched.com/event/29f478bfe32ba9420233380c23ff67af
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T142000Z
DTEND:20260616T144000Z
SUMMARY:Break
DESCRIPTION:
CATEGORIES:BREAK
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:770799856099c56fd5002312fff6992a
URL:http://ucgissymposium2026.sched.com/event/770799856099c56fd5002312fff6992a
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T144000Z
DTEND:20260616T160000Z
SUMMARY:Student Lightning Talks: Emerging Directions in GeoAI
DESCRIPTION:Cluster 1: Urban Perception & Human-Centered AI\n Keenon Lindsey\, Texas State Univ.: “Seeing” Gentrification: A Deep Learning Approach to Visual Change Perception\n Yingrui Zhao\, Univ. of Maryland: An LLM-Guided Approach for Analyzing Public Sentiment associated with Transportation POI Visit Patterns\n Michaelmary Chukwu\, Univ. of Maryland: From Gravity Models to Semantic Reasoning: Leveraging LLMs for Visual Destination Characterization\n \nCluster 2: Environment\, Hazards & Remote Sensing\n Sandra Le\, George Mason Univ.: A Spatiotemporal Analysis of Vegetation and Water Changes in Libya Extreme Rainfall 2023 Using Remote Sensing Products and the Google Earth Engine (GEE)\n Xin Dong\, Univ. of Maryland: Predicting the spatio-temporal spread of Plasmodium vivax malaria using a human-movement–informed GeoAI model\n Aleksander Berg\, Univ. of Colorado Boulder: Using Foundation Model Embeddings to Map Colorado's Built Hazard Interface for Wildfire\n\n — Break / Reset (5 min.) —\n \nCluster 3: GeoAI Methods & Modeling\n Jikun Liu\, Texas A&M Univ.: A Wide-and-Deep-Based Time Sequence Model for Predicting Power Outages Caused by Extreme Winter Storms\n Victor Irekponor\, Univ. of Maryland: Text-to-Visualization for Spatially Varying Coefficient Models: Encoding SVC Visualization Principles in Language-Driven Workflows\n Zhihao Wang\, Univ. of Maryland: TreeFinder: AI Everywhere in Forest Monitoring — A National-Scale GeoAI Benchmark for Individual Tree Mortality\n \nCluster 4: Spatial Theory & Advanced Methods\n Mengyu Liao\, Univ. of Maryland: Change of Support as a Reasoning Layer in LLM-Based GIS Workflows\n Jina&nbsp\;Kim\, Univ. of Minnesota: Spatial Heterogeneity-Aware Cross-Indicator Transfer for Prediction in Label-Sparse Regions\n\n
CATEGORIES:LIGHTNING TALK
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:0e1c50131e610b215a823399a4e94d12
URL:http://ucgissymposium2026.sched.com/event/0e1c50131e610b215a823399a4e94d12
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T144000Z
DTEND:20260616T160000Z
SUMMARY:State of the Industry
DESCRIPTION:Moderated by Aaron Addison\, WGIC Executive Director
CATEGORIES:PANEL
LOCATION:TBA\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:ad6fad51046b9f223e23d9cb2d21293f
URL:http://ucgissymposium2026.sched.com/event/ad6fad51046b9f223e23d9cb2d21293f
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T160000Z
DTEND:20260616T173000Z
SUMMARY:Lunch
DESCRIPTION:
CATEGORIES:MEAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:061c10da3ad6145b75eb575c8108f663
URL:http://ucgissymposium2026.sched.com/event/061c10da3ad6145b75eb575c8108f663
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T173000Z
DTEND:20260616T190000Z
SUMMARY:Student papers B: Environmental & Hazard Applications
DESCRIPTION:Omada Friday Ojonugwa\, Beihang Univ.: Multi-Sensor Fusion for Soil Moisture Estimation in West Africa using Ensemble Learning\n Paul C. Dunn\, Oregon State Univ.: Retrieval-Augmented 4D Visualization for a Digital Twin of the Ocean: Improving Multiscale Pattern–Process Analysis with Generative AI\, Reinforcement Learning\, and Heterogeneous I/O\n Youshuang Hu\, Univ. of Connecticut: GISc for Social Equity: Unpacking the Black Box of Multidimensional Impact of Structural Racism and Discrimination
CATEGORIES:RESEARCH PAPER
LOCATION:Room B\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:f44a9854c7cb18340d47d593054f1e75
URL:http://ucgissymposium2026.sched.com/event/f44a9854c7cb18340d47d593054f1e75
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T173000Z
DTEND:20260616T190000Z
SUMMARY:Student Papers Session A: GeoAI Methods & Modeling
DESCRIPTION:Yue Liu\, Auburn Univ.: A Graph Neural Network Approach for Spatial Prediction of Urban Heat Islands\n Hafiz Tayyab Khattak\, Auburn Univ.: Integrating Deep Learning and GIS for High-Resolution Flood Susceptibility Mapping\n Zihan Chen\, UC Santa Barbara: Spatiotemporal Modeling of Wildfire Risk Using GeoAI Techniques\n Rishabh Sachdeva\, Univ. of Florida: A Hybrid Machine Learning Framework for Land Use Change Detection
CATEGORIES:RESEARCH PAPER
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:2bd55bd08d0bd7985805f632a87f3cc4
URL:http://ucgissymposium2026.sched.com/event/2bd55bd08d0bd7985805f632a87f3cc4
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T190000Z
DTEND:20260616T193000Z
SUMMARY:Break
DESCRIPTION:
CATEGORIES:BREAK
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:e56cc6e4a1a3000eced661aa10fd8bae
URL:http://ucgissymposium2026.sched.com/event/e56cc6e4a1a3000eced661aa10fd8bae
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T193000Z
DTEND:20260616T210000Z
SUMMARY:Student papers C: Urban Systems & Human-Centered GeoAI
DESCRIPTION:Shirin Alsadat Mahmoudian\, George Mason Univ.: Generative AI for Urban Infrastructure Auditing: A Micro-scale Evaluation of Multimodal Transit Environments\n Isaac Quaye\, Temple Univ.: Explainability of DL-based Gentrification Detection from Street View Imagery\n Jon Nealon\, SUNY Albany: Beyond the God's Eye View: The Hot Air Balloon Perspective in Geospatial Journalism
CATEGORIES:RESEARCH PAPER
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:d03cb054cffda1470d157ead95184cad
URL:http://ucgissymposium2026.sched.com/event/d03cb054cffda1470d157ead95184cad
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T193000Z
DTEND:20260616T210000Z
SUMMARY:Student papers D: Spatial Analysis and Emerging Applications in GIScience
DESCRIPTION:Hailey Richardson\, Univ. of Alabama: Understanding the Impact of Spatial Relationship Definitions on Crime Clustering Analysis: Implications for Urban Crime Patterns and Policing Strategies\n Youshuang Hu\, Univ. of Connecticut: GIScience for Social Equity: Unpacking the Black Box of Spatial Inequality\n Yuán Niú\, Texas A&M Univ.: A Spatial Decision-Support Tool to Enhance Participatory Planning for Urban Heat Resilience\n Madhukar Kuchavaram\, Univ. of Florida: Spatiotemporal Forecasting for Proactive Vector Control
CATEGORIES:RESEARCH PAPER
LOCATION:Room B\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:d8d6da0bc19a0c28055158b0d94eb63f
URL:http://ucgissymposium2026.sched.com/event/d8d6da0bc19a0c28055158b0d94eb63f
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260616T223000Z
DTEND:20260617T003000Z
SUMMARY:Poster Session + Opening Reception
DESCRIPTION:Students\nJayanta Biswas\, UNC Charlotte: A Deep Learning Framework for Fusing Multi-Modal Environmental Data to Downscale Human Mobility for Precision Malaria Modeling in Zambia\n Arati Budhathoki\, Clemson Univ.: Tracking Mountain Degradation for the United Nations (UN) Sustainable Development Goals (SDGs) Using the State of Colorado (USA) as an Example\n Sofiia Drozd\, NTUU KPI: Agentic AI Framework for Automated Mapping of War-Damaged Agricultural Risk Zones and Satellite Data Retrieval\n Paul C. Dunn\, Oregon State Univ.: Improving Multiscale Pattern–Process Analysis with a Eulerian-Lagrangian Flow Model and Uncertainty Aware Clustering Analysis\n Maxwell Gundling\, Salisbury Univ.: From Silos to Spatial Data: An Enterprise GIS for Historical Research\nFatemeh Janatabadi\, George Mason Univ.: Artificial Intelligence Drives a New Feedback Loop Between Human Mobility and Urban Landscapes \nSiyu&nbsp\;Lu\,&nbsp\;Texas A&M Univ.: Deep Learning versus Traditional Interpolation for Elevation Reconstruction: Evaluating Performance Gains from Terrain-Based Auxiliary Variables \nOliver Matus-Bond\, Macalester College: Mapping the spatial relationship between invasive Melaleuca quinquenervia and fire occurrence in southeastern Madagascar \n Haley Mullen\, Univ. of Maryland: LLM-based generation of geospatial synthetic data for predicting chronic disease\n Hossein Naderi\, Texas A&M Univ.–Corpus Christi: Using Large Language Models to Quantify Urban Environments from Google Street View\n Zahra Salehi\, Univ. of Connecticut: Spatial Intelligence for Agrivoltaic Land Suitability: A GIS-Based Multi-Criteria Decision Framework in Connecticut\n Rachel Simon\, Salisbury Univ.: From Surface to Subsurface: Mapping Cemeteries in Dorchester County\, Maryland\n Daryna Skakun\, Urbana High School: Agentic AI for Environmental Impact Assessment of Construction Projects Using Satellite Data\n Ruichen Wang\, Univ. of Maryland: Coincident Data Discovery Engine (CoDD): Enabling Global Cross-Platform Satellite Data Discovery\n Zhihao Wang\, Univ. of Maryland: CarbonGlobe: A Global ML-Ready Benchmrk for Long-Term Carbon Forecasting Under Climate Change \n\nFaculty & Other\n Wataru Morioka\, Salisbury Univ.: Spatial Thinking–Centered GIS Curriculum: Problem Solving\, Collaboration\, and AI Era Pedagogy at Salisbury University\n\n
CATEGORIES:POSTER SESSION
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:18add1c03ecb669e4a940e2cb9464bef
URL:http://ucgissymposium2026.sched.com/event/18add1c03ecb669e4a940e2cb9464bef
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T120000Z
DTEND:20260617T130000Z
SUMMARY:Continental Breakfast
DESCRIPTION:
CATEGORIES:MEAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:c9a307558e3d514babc3ee5c0b614952
URL:http://ucgissymposium2026.sched.com/event/c9a307558e3d514babc3ee5c0b614952
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T132000Z
DTEND:20260617T142000Z
SUMMARY:Plenary Session: Scaling over Space: Advancing the Model and Data Foundations of GeoAI
DESCRIPTION:Scaling over Space: Advancing the Model and Data Foundations of GeoAI\nAdvances in deep learning and foundation models are raising expectations for general-purpose learning and creating new opportunities to harness the geospatial data revolution for Earth monitoring and scientific discovery\, with broad benefits for agriculture\, energy\, water\, transportation\, smart cities\, and disaster response. At the same time\, major challenges remain for large-scale geospatial applications\, including spatial variability that substantially weakens model generalization\, limited and localized training data\, and high computational demands that constrain and slow scientific discovery. This talk will discuss both AI model and data foundations for scaling geospatial applications\, including geo-aware learning\, knowledge-guided learning\, task-aligned pretraining\, and new benchmark datasets.\n
CATEGORIES:PLENARY
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:670468d12c95204d59c263f49c4c8ef6
URL:http://ucgissymposium2026.sched.com/event/670468d12c95204d59c263f49c4c8ef6
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T141000Z
DTEND:20260617T143000Z
SUMMARY:Break
DESCRIPTION:
CATEGORIES:BREAK
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:af77fc2f2022bf56fc1c83c0690ad1e7
URL:http://ucgissymposium2026.sched.com/event/af77fc2f2022bf56fc1c83c0690ad1e7
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T143000Z
DTEND:20260617T160000Z
SUMMARY:Developing Your GIS Professional Ecosystem: Associations\, Networks\, and Career Pathways
DESCRIPTION:Join us for a session on growing your network and career!\n\nEsri: Michelle Kinzer \nGPN: Sid Pandey \nASPRS: Karen Schuckman \nWiGIS: Eva Reid \nGISCI: Jochen Albrecht
CATEGORIES:PANEL
LOCATION:Room B\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:cd958f238086f82ead9684a58ddcb2de
URL:http://ucgissymposium2026.sched.com/event/cd958f238086f82ead9684a58ddcb2de
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T143000Z
DTEND:20260617T160000Z
SUMMARY:Research Highlights: Advances in GeoAI and Spatial Modeling
DESCRIPTION:Sergii Skakun\, Univ. of Maryland: ON THE INFERENCE FROM SATELLITE-BASED CLASSIFICATION MAPS FOR AREA ESTIMATION\n Luyu Liu\, Texas A&M Univ.: Disentangling and Tackling the Spatiotemporal Biases in Social Sensing Data: A Cognitive-behavioral Approach\n Jielu Zhang\, Harvard Univ.: SpatialCausal: a spatially-aware causal inference deep learning model for out-of-hospital cardiac arrest survival prediction\n Mehak Sachdeva\, Florida State Univ.: Simulating the Precursor: Generative AI and Counterfactual Scenario Modeling of Partisan Mobility and Spatial Segregation
CATEGORIES:RESEARCH PAPER
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:0ce2ffc3ca19b66b178ba201b61c56c3
URL:http://ucgissymposium2026.sched.com/event/0ce2ffc3ca19b66b178ba201b61c56c3
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T160000Z
DTEND:20260617T173000Z
SUMMARY:Lunch
DESCRIPTION:
CATEGORIES:MEAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:f0be036c12b8a5adb3863020962ea8da
URL:http://ucgissymposium2026.sched.com/event/f0be036c12b8a5adb3863020962ea8da
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T173000Z
DTEND:20260617T190000Z
SUMMARY:Humans in GeoAI
DESCRIPTION:This panel session aims to engage both panelists and the audience in a critical dialogue about the challenges\, opportunities\, and paths forward regarding the relationship between humans and GIS/GeoAI. We seek to explore how to develop a human-centered vision of GIScience and GeoAI that is both socially responsible and cognitively informed.
CATEGORIES:PANEL
LOCATION:Room B\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:b37bbfd58f85f65a1efc18de0b7072ba
URL:http://ucgissymposium2026.sched.com/event/b37bbfd58f85f65a1efc18de0b7072ba
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T173000Z
DTEND:20260617T190000Z
SUMMARY:Research Highlights and Lightning Talks: Emerging Methods and Applications in GeoAI
DESCRIPTION:Full Research Presentations\n Somayeh Dodge\, UC Santa Barbara: What Mobile Location Data Can Tell Us About Nature Exposure?\n Isaac Rand\, Federal Reserve Bank of Philadelphia: Automated Digitization of the Censuses of Housing Block Statistics\, 1940-1970 \n\n Lightning Talks\n Xuebin Wei\, James Madison Univ.: Building an AI Teaching Stack for GeoAI Education\n Peter Kedron\, UC Santa Barbara: Spatial Reasoning and identification in Causal Inference\n Lei Song\, Rutgers Univ.: Explainable AI Reveals How Precipitation Modulates Thermal Effects Across Vertebrates\n Elizabeth Newnam\, Temple Univ.: Effects of NDVI Exposure on Cannabis Use Disorder Treatment \n\n
CATEGORIES:RESEARCH PAPER
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:cf4d2879b68f3489cfa313dffc640f24
URL:http://ucgissymposium2026.sched.com/event/cf4d2879b68f3489cfa313dffc640f24
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T190000Z
DTEND:20260617T193000Z
SUMMARY:Break
DESCRIPTION:
CATEGORIES:BREAK
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:2bb5fbad46288f5fc2e0a27140aec28d
URL:http://ucgissymposium2026.sched.com/event/2bb5fbad46288f5fc2e0a27140aec28d
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T193000Z
DTEND:20260617T210000Z
SUMMARY:Field Trip: Maryland Robotics Center
DESCRIPTION:
CATEGORIES:FIELD TRIP
LOCATION:Offsite\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:33cc31502c28c3f3880d528dfceba313
URL:http://ucgissymposium2026.sched.com/event/33cc31502c28c3f3880d528dfceba313
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T193000Z
DTEND:20260617T210000Z
SUMMARY:CaGIS Student Paper Competition
DESCRIPTION:Ju He\, Florida State Univ.: Estimating the Continuous Causal Effect of Spatial Distance on Outcomes\n Chen Zhang\, Univ. of Connecticut: CASTED: Calibrated Anomaly-based Spatial-Temporal Event Detection Framework for Anomaly Detection in Resilience Curves\n Farnoosh Roozkhosh\, Univ. of Georgia: Context-Augmented GeoAI for Public EV Charging: Predicting When and Where Charging Occurs\n Tongwei Xu\, Univ. of Washington: The Geography of “AI Slop”: An Embedding-Based Spatial Analysis of AI-Generated Music\n Tang Sui\, Univ. of Wisconsin–Madison: FireST-GraphNet: Wildfire Progression Prediction via a Temporal Graph Neural Network with Sequence Learning
CATEGORIES:RESEARCH PAPER
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:5a2c86a8b5c9f67f1d32e6f79c7ccffc
URL:http://ucgissymposium2026.sched.com/event/5a2c86a8b5c9f67f1d32e6f79c7ccffc
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260617T223000Z
DTEND:20260618T003000Z
SUMMARY:Board Dinner
DESCRIPTION:
CATEGORIES:SOCIAL
LOCATION:Offsite\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:4598319defb8f88c1dfe6c00ffaf549c
URL:http://ucgissymposium2026.sched.com/event/4598319defb8f88c1dfe6c00ffaf549c
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T120000Z
DTEND:20260618T130000Z
SUMMARY:Continental Breakfast
DESCRIPTION:
CATEGORIES:MEAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:f32a1e960f5fbe2b628f2c74c27b4904
URL:http://ucgissymposium2026.sched.com/event/f32a1e960f5fbe2b628f2c74c27b4904
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T130000Z
DTEND:20260618T142000Z
SUMMARY:Plenary Panel: AI in Geospatial Education
DESCRIPTION:
CATEGORIES:PLENARY
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:758329cdd18db2e560024cf0ef65a219
URL:http://ucgissymposium2026.sched.com/event/758329cdd18db2e560024cf0ef65a219
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T142000Z
DTEND:20260618T144000Z
SUMMARY:Break
DESCRIPTION:
CATEGORIES:BREAK
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:3ea3f1c3cf5107368a58787a8c488bdb
URL:http://ucgissymposium2026.sched.com/event/3ea3f1c3cf5107368a58787a8c488bdb
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T144000Z
DTEND:20260618T154500Z
SUMMARY:Awards Ceremony
DESCRIPTION:
CATEGORIES:SOCIAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:7f1571d5146a8d54016532feceeee98a
URL:http://ucgissymposium2026.sched.com/event/7f1571d5146a8d54016532feceeee98a
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T154500Z
DTEND:20260618T173000Z
SUMMARY:Council Lunch
DESCRIPTION:
CATEGORIES:MEAL
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:a85e70a2f1c54e20787d6433d026e383
URL:http://ucgissymposium2026.sched.com/event/a85e70a2f1c54e20787d6433d026e383
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T173000Z
DTEND:20260618T190000Z
SUMMARY:Education Session
DESCRIPTION:
CATEGORIES:PANEL
LOCATION:Room B\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:60d51421533b9f0c0bc33b87122ef86c
URL:http://ucgissymposium2026.sched.com/event/60d51421533b9f0c0bc33b87122ef86c
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T173000Z
DTEND:20260618T190000Z
SUMMARY:Federal Agencies Panel
DESCRIPTION:
CATEGORIES:PANEL
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:127c2fdd89221d6167fc05f9efa46311
URL:http://ucgissymposium2026.sched.com/event/127c2fdd89221d6167fc05f9efa46311
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T190000Z
DTEND:20260618T193000Z
SUMMARY:Break
DESCRIPTION:
CATEGORIES:BREAK
LOCATION:Main\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:80e713b2ae6c7f066775bc067a4bf367
URL:http://ucgissymposium2026.sched.com/event/80e713b2ae6c7f066775bc067a4bf367
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T193000Z
DTEND:20260618T210000Z
SUMMARY:Field Trip
DESCRIPTION:
CATEGORIES:FIELD TRIP
LOCATION:Offsite\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:68dcf10a81d9d0ebbb518b5f81dd7562
URL:http://ucgissymposium2026.sched.com/event/68dcf10a81d9d0ebbb518b5f81dd7562
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T042903Z
DTSTART:20260618T193000Z
DTEND:20260618T210000Z
SUMMARY:Golden Compass Session
DESCRIPTION:
CATEGORIES:PANEL
LOCATION:Room A\, Edward St. John Learning and Teaching Center\, Campus Drive\, College Park\, MD\, US
SEQUENCE:0
UID:6ee4501ec4e46119d781b1c68e431e3f
URL:http://ucgissymposium2026.sched.com/event/6ee4501ec4e46119d781b1c68e431e3f
END:VEVENT
END:VCALENDAR