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Traffic prediction during hurricane evacuation is essential for optimizing the use of transportation infrastructures. It can reduce evacuation time by providing information on future congestion in advance. However, evacuation traffic…
Resource allocation under uncertainty is a classical problem in city-scale cyber-physical systems. Consider emergency response as an example; urban planners and first responders optimize the location of ambulances to minimize expected…
The Epidemic-Type Aftershock Sequences (ETAS) model and its variants effectively capture the space-time clustering of seismicity, setting the standard for earthquake forecasting. Accurate unbiased ETAS calibration is thus crucial. But we…
According to the United States High Commission for Refugees (UNHCr), there are 65.3 million forcibly displaced people in the world today, 21.5 million of them being refugees. This has led to an unprecedented refugee crisis which has led…
In the face of a pandemic, urban protests, and an affordability crisis, is the desirability of dense urban settings at a turning point? Assessing cities' long term trends remains challenging. The first part of this chapter describes the…
In many developing countries, half the population lives in rural locations, where access to essentials such as school materials, mosquito nets, and medical supplies is restricted. We propose an alternative method of distribution (to…
This paper presents a data-driven approach for quantifying the resilience of distribution power grids to extreme weather events using two key metrics: (a) the number of outages and (b) restoration time. The method leverages historical…
Understanding the travel challenges faced by low-income residents has always been and continues to be one of the most important transportation equity topics. This study aims to explore the mobility gaps between low-income households (HHs)…
The Simplified Access Metric (SAM) is a new approach for characterizing emergency shelter access patterns as a measure of shelter client vulnerability. The goal of SAM is to provide shelter operators with an intuitive way to understand…
This paper reviews the literature on response strategies for restoring infrastructure networks in the aftermath of a disaster. Our motivation for this review is twofold. First, the frequency and magnitude of natural and man-made disasters…
Dispatching mobile resources such as repair crews and mobile emergency generators is essential for the rapid restoration of distribution systems after extreme events. However, the restoration process is affected by various uncertain factors…
We present a method to learn mean residence time and escape probability from data modeled by stochastic differential equations. This method is a combination of machine learning from data (to extract stochastic differential equations as…
We use wireless voice-call and text-message volumes to quantify spatiotemporal communication patterns in the New York Metro area before, during, and after the Virginia earthquake and Hurricane Irene in 2011. The earthquake produces an…
Electric power network expanded rapidly in recent decades due of the excessive need of electricity in every aspect of life, including critical infrastructures such as medical services, and transportation and communication systems. Natural…
As Earth's climate changes, it is impacting disasters and extreme weather events across the planet. Record-breaking heat waves, drenching rainfalls, extreme wildfires, and widespread flooding during hurricanes are all becoming more frequent…
We study the problem of allocating scarce societal resources of different types (e.g., permanent housing, deceased donor kidneys for transplantation, ventilators) to heterogeneous allocatees on a waitlist (e.g., people experiencing…
Disasters are constant threats to humankind, and beyond losses in lives, they cause many implicit yet profound societal issues such as wealth disparity and digital divide. Among those recovery measures in the aftermath of disasters,…
We develop a statistical method for identifying induced seismicity from large datasets and apply the method to decades of wastewater disposal and seismicity data in California and Oklahoma. The method is robust against a variety of…
We investigate fluid transport in random velocity fields with unsteady drift. First, we propose to quantify fluid transport between flow regimes of different characteristic motion, by escape probability and mean residence time. We then…
In this work we consider a stochastic movement process with random resets to the origin followed by a random residence time there before the walker restarts its motion. First, we study the transport properties of the walker, we derive an…