53 citations · 57 across the 10 of their papers we have counts for
12 papers
Leveraging Large Language Models for Systematic Literature Review of Disease Spread Models
Orhan Yagizer Cinar, Timur Emre Ozkose, Emma Von Hoene +3
Recent advancements in Large Language Models (LLMs) have created new opportunities to streamline and potentially automate many research processes, including systematic literature r…
SF-LIFE: A Large-Scale Simulated Movement Dataset for the San Francisco Bay Area
Chanuka Algama, Taylor Anderson, Henrique Ferraz de Arruda +14
We introduce SF-LIFE, a large-scale simulated movement dataset designed to accelerate research in transportation, mobility, and machine learning. The dataset contains 3,024,000,000…
Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis
Taylor Anderson, Sara Von Hoene, Orhan Yagizer Cinar +4
There is a growing interest in utilizing synthetic populations for a diverse range of applications. At the same time, we are witnessing a tremendous growth in artificial intelligen…
Towards Universal Urban Patterns-of-Life Simulation
Sandro M. Reia, Henrique F. de Arruda, Shiyang Ruan +3
Understanding urban mobility requires models that capture how people interact with and navigate the built environment. We present a scalable, generalizable agent-based framework in…
HD-GEN: A High-Performance Software System for Human Mobility Data Generation Based on Patterns of Life
Hossein Amiri, Joon-Seok Kim, Hamdi Kavak +4
Understanding individual-level human mobility is critical for a wide range of applications. Real-world trajectory datasets provide valuable insights into movement behaviors and pat…
Evaluation of A Spatial Microsimulation Framework for Small-Area Estimation of Population Health Outcomes Using the Behavioral Risk Factor Surveillance System
Emma Von Hoene, Aanya Gupta, Hamdi Kavak +2
This study introduces the Spatial Health and Population Estimator (SHAPE), a spatial microsimulation framework that applies hierarchical iterative proportional fitting (IPF) to est…
All Models Are Wrong, But Can They Be Useful? Lessons from COVID-19 Agent-Based Models: A Systematic Review
Emma Von Hoene, Sara Von Hoene, Szandra Peter +9
The COVID-19 pandemic prompted a surge in computational models to simulate disease dynamics and guide interventions. Agent-based models (ABMs) are well-suited to capture population…
The Patterns of Life Human Mobility Simulation
Hossein Amiri, Will Kohn, Shiyang Ruan +6
We demonstrate the Patterns of Life Simulation to create realistic simulations of human mobility in a city. This simulation has recently been used to generate massive amounts of tr…
Extracting the U.S. building types from OpenStreetMap data
Henrique F. de Arruda, Sandro M. Reia, Shiyang Ruan +4
Building type information is crucial for population estimation, traffic planning, urban planning, and emergency response applications. Although essential, such data is often not re…
Function and form of U.S. cities
Sandro M. Reia, Taylor Anderson, Henrique F. Arruda +4
The relationship between urban form and function is a complex challenge that can be examined from multiple perspectives. In this study, we propose a method to characterize the urba…
A general epidemic model and its application to mask design considering different preferences towards masks
Chaoqian Wang, Hamdi Kavak
While most masks have a limited effect on personal protection, how effective are they for collective protection? How to enlighten the design of masks from the perspective of collec…
Change of human mobility during COVID-19: A United States case study
Justin Elarde, Joon-Seok Kim, Hamdi Kavak +2
With the onset of COVID-19 and the resulting shelter in place guidelines combined with remote working practices, human mobility in 2020 has been dramatically impacted. Existing stu…