activity
20242026
collaborators

7 papers

cs.LG2026

IBAD: Interpretable Behavioral Anomaly Detection on Human Mobility Data

Bita Azarijoo, John Krumm, Cyrus Shahabi

Human mobility appears highly diverse, yet much of a person's daily mobility can be explained by a small set of recurring behavioral templates, such as commuting, school-centered a…

cs.CV2025

OSMGen: Highly Controllable Satellite Image Synthesis using OpenStreetMap Data

Amir Ziashahabi, Narges Ghasemi, Sajjad Shahabi +3

Accurate and up-to-date geospatial data are essential for urban planning, infrastructure monitoring, and environmental management. Yet, automating urban monitoring remains difficul…

cs.LG2025

NEXICA: Discovering Road Traffic Causality (Extended arXiv Version)

Siddharth Srikanth, John Krumm, Jonathan Qin

Road traffic congestion is a persistent problem. Focusing resources on the causes of congestion is a potentially efficient strategy for reducing slowdowns. We present NEXICA, an al…

cs.LG2025

Poly2Vec: Polymorphic Fourier-Based Encoding of Geospatial Objects for GeoAI Applications

Maria Despoina Siampou, Jialiang Li, John Krumm +2

Encoding geospatial objects is fundamental for geospatial artificial intelligence (GeoAI) applications, which leverage machine learning (ML) models to analyze spatial information.…

cs.AI2025

Geo-Llama: Leveraging LLMs for Human Mobility Trajectory Generation with Spatiotemporal Constraints

Siyu Li, Toan Tran, Haowen Lin +5

Generating realistic human mobility data is essential for various application domains, including transportation, urban planning, and epidemic control, as real data is often inacces…

cs.LG2024

TrajGPT: Controlled Synthetic Trajectory Generation Using a Multitask Transformer-Based Spatiotemporal Model

Shang-Ling Hsu, Emmanuel Tung, John Krumm +2

Human mobility modeling from GPS-trajectories and synthetic trajectory generation are crucial for various applications, such as urban planning, disaster management and epidemiology…