activity
20202023
most citedA Network Percolation-based Contagion Model of Flood Propagation and Recession in Urban Road Networks

53 citations · 150 across the 34 of their papers we have counts for

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Showing physics.soc-phShow all

19 papers · 1 filter

physics.soc-ph20223 cited

Anatomy of Perturbed Traffic Networks during Urban Flooding

Akhil Anil Rajput, Sanjay Nayak, Shangjia Dong +1

Urban flooding disrupts traffic networks, affecting the mobility and disrupting access of residents. Since flooding events are predicted to increase due to climate change, and give…

physics.soc-ph20224 cited

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…

physics.soc-ph20228 cited

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…

physics.soc-ph20211 cited

Revealing the Global Linguistic and Geographical Disparities of Public Awareness to Covid-19 Outbreak through Social Media

Binbin Lin, Lei Zou, Nick Duffield +7

The Covid-19 has presented an unprecedented challenge to public health worldwide. However, residents in different countries showed diverse levels of Covid-19 awareness during the o…

physics.soc-ph20219 cited

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…

physics.soc-ph20216 cited

Predicting Road Flooding Risk with Machine Learning Approaches Using Crowdsourced Reports and Fine-grained Traffic Data

Faxi Yuan, William Mobley, Hamed Farahmand +5

The objective of this study is to predict road flooding risks based on topographic, hydrologic, and temporal precipitation features using machine learning models. Predictive flood…