53 citations · 114 across the 19 of their papers we have counts for
19 papers
Dynamics of Collective Information Processing for Risk Encoding in Social Networks during Crises
Chao Fan, Fangsheng Wu, Ali Mostafavi
Online social networks are increasingly being utilized for collective sense making and information processing in disasters. However, the underlying mechanisms that shape the dynami…
Chasing Fairness in Graphs: A GNN Architecture Perspective
Zhimeng Jiang, Xiaotian Han, Chao Fan +4
There has been significant progress in improving the performance of graph neural networks (GNNs) through enhancements in graph data, model architecture design, and training strateg…
FairMobi-Net: A Fairness-aware Deep Learning Model for Urban Mobility Flow Generation
Zhewei Liu, Lipai Huang, Chao Fan +1
Generating realistic human flows across regions is essential for our understanding of urban structures and population activity patterns, enabling important applications in the fiel…
Mobility Behaviors Shift Disparity in Flood Exposure in U.S. Population Groups
Bo Li, Chan Fan, Yu-Heng Chien +2
Current characterization of flood exposure is largely based on residential location of populations; however, location of residence only partially captures the extent to which popul…
Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes
Junwei Ma, Bo Li, Qingchun Li +2
The spread of COVID-19 revealed that transmission risk patterns are not homogenous across different cities and communities, and various heterogeneous features can influence the spr…
Human Mobility Disproportionately Extends PM2.5 Emission Exposure for Low Income Populations
Chao Fan, Yu-Heng Chien, Ali Mostafavi
Ambient exposure to fine particulate matters of diameters smaller than 2.5μm (PM2.5) has been identified as one critical cause for respiratory disease. Disparities in exposure to P…
Quantitative Measures for Integrating Resilience into Transportation Planning Practice: Study in Texas
Cheng-Chun Lee, Akhil Rajput, Chia-Wei Hsu +10
The objective of this study is to propose a system-level framework with quantitative measures to assess the resilience of road networks. The framework proposed in this paper can he…
FMP: Toward Fair Graph Message Passing against Topology Bias
Zhimeng Jiang, Xiaotian Han, Chao Fan +4
Despite recent advances in achieving fair representations and predictions through regularization, adversarial debiasing, and contrastive learning in graph neural networks (GNNs), t…
Smart Flood Resilience: Harnessing Community-Scale Big Data for Predictive Flood Risk Monitoring, Rapid Impact Assessment, and Situational Awareness
Faxi Yuan, Chao Fan, Hamed Farahmand +7
Smart resilience is the beneficial result of the collision course of the fields of data science and urban resilience to flooding. The objective of this study is to propose and demo…
Neural Embeddings of Urban Big Data Reveal Emergent Structures in Cities
Chao Fan, Yang Yang, Ali Mostafavi
In this study, we propose using a neural embedding model-graph neural network (GNN)- that leverages the heterogeneous features of urban areas and their interactions captured by hum…
Limitations of gravity models in predicting fine-scale spatial-temporal urban mobility networks
Chiawei Hsu, Chao Fan, Ali Mostafavi
This study identifies the limitations and underlying characteristics of urban mobility networks that influence the performance of the gravity model. The gravity model is a widely-u…
Data-driven Contact Network Models of COVID-19 Reveal Trade-offs between Costs and Infections for Optimal Local Containment Policies
Chao Fan, Xiangqi Jiang, Ronald Lee +1
While several non-pharmacological measures have been implemented for a few months in an effort to slow the coronavirus disease (COVID-19) pandemic in the United States, the disease…
Unraveling the Dynamic Importance of County-level Features in Trajectory of COVID-19
Qingchun Li, Yang Yang, Wangqiu Wang +6
The objective of this study was to investigate the importance of multiple county-level features in the trajectory of COVID-19. We examined feature importance across 2,787 counties…
Early Indicators of COVID-19 Spread Risk Using Digital Trace Data of Population Activities
Xinyu Gao, Chao Fan, Yang Yang +4
The spread of pandemics such as COVID-19 is strongly linked to human activities. The objective of this paper is to specify and examine early indicators of disease spread risk in ci…
Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises
Chao Fan, Xiangqi Jiang, Ali Mostafavi
The objective of this study is to propose and test an adaptive reinforcement learning model that can learn the patterns of human mobility in a normal context and simulate the mobil…
DeepCOVIDNet: An Interpretable Deep Learning Model for Predictive Surveillance of COVID-19 Using Heterogeneous Features and their Interactions
Ankit Ramchandani, Chao Fan, Ali Mostafavi
In this paper, we propose a deep learning model to forecast the range of increase in COVID-19 infected cases in future days and we present a novel method to compute equidimensional…
Disparate Patterns of Movements and Visits to Points of Interests Located in Urban Hotspots across U.S. Metropolitan Cities during COVID-19
Qingchun Li, Liam Bessell, Xin Xiao +3
We examined the effect of social distancing on changes in visits to urban hotspot points of interest. Urban hotspots, such as central business districts, are gravity activity cente…
Effects of Population Co-location Reduction on Cross-county Transmission Risk of COVID-19 in the United States
Chao Fan, Sanghyeon Lee, Yang Yang +3
The rapid spread of COVID-19 in the United States has imposed a major threat to public health, the real economy, and human well-being. With the absence of effective vaccines, the p…
A Network Percolation-based Contagion Model of Flood Propagation and Recession in Urban Road Networks
Chao Fan, Xiangqi Jiang, Ali Mostafavi
In this study, we propose a contagion model as a simple and powerful mathematical approach for predicting the spatial spread and temporal evolution of the onset and recession of fl…