Today I am officially a full professor! I’ve had a wonderful journey as a professor. Below I pasted my research statement that summarizes all of the research I’ve done since my PhD. I thought this was worth sharing with people other than my colleagues on the promotions committee.
My research applies operations research methodologies to important societal applications. My primary methodological base is discrete optimization, including integer programming and Markov decision processes (MDPs). I have applied operations research methodologies to address public sector problems related to emergency medical services, homeland security and infrastructure protection, and disaster response and recovery.
The public sector applications I have studied are complex systems that span people, processes, vehicles, and critical infrastructure. My research has studied how to cost-effectively allocate resources, decisions that are not made in isolation. Rather, decisions are interrelated, with every decision potentially affecting every other decision due to congestion, processing delays, capacities, and uncertainty about what can happen next. While many papers in the literature apply operations research methods to public sector problems, these papers have limitations. First, research models make simplifying assumptions that limit the applicability of the research to real systems. Second, the papers in the literature have not been adequate for addressing problems in emerging areas, such as in homeland security, infrastructure protection, and disaster management, which have become important issues of national concern in recent years.
To overcome these limitations, I have identified problems that are important from a societal point of view and interesting from a methodological point of view. My approach has been to either lift simplifying assumptions made in the literature to broaden the scope of applicability and/or formulate new models to represent problems not yet considered in the literature. Moreover, I have worked with stakeholders to gain domain expertise and have used real-world data whenever possible to ensure that the most salient aspects of the problems are reflected in my models and analysis.
My research has made several substantive and technical contributions to operations research and public sector applications. I have identified important public sector problems that have not been addressed in the literature and can be modeled using operations research techniques, thereby expanding the operations research discipline to encompass new applications that motivate new models and solution techniques. I typically formulate a new optimization model for each problem at hand, drawing on methods and ideas relevant to the application, since one generic model cannot be meaningfully applied to many settings. I have employed a broad set of methods, drawing from integer programming, stochastic programming, network optimization, network interdiction, MDPs, and queueing, since a broad methodological toolkit is essential for solving real problems. I have analyzed each of the models to provide insights about a particular problem, facilitate numerical implementation, and identify exact and heuristic algorithmic approaches. Finally, I solve the models, using real-world data or representative data sets.
My emergency medical service (EMS) research dates to 2007 and focuses on how to enhance emergency healthcare by deploying and routing multiple types of vehicles to emergency calls for service. I formed a community partnership with local fire and EMS departments, and these collaborations provided the motivation and domain knowledge for my research. While there exist many models for EMS planning in the literature, most models assume a uniform fleet of homogenous ambulances and do not consider prioritized patients. My research has lifted these assumptions to design risk-based planning and response protocols using a heterogeneous set of vehicles to and to gain policy insights. My research has led to an analysis of performance measures to support patient outcomes and survivability, new models for informing ambulance deployment and routing decisions, and new insights for balancing multiple criteria in making these decisions. My research on deploying non-transport vehicles to emergency healthcare patients was the first of its kind, which led to important policy insights for public safety leaders. This research was put into practice by Hanover County Fire & EMS in Virginia. I was part of the Hanover County team that was awarded a National Association of Counties (NACo) award in 2010: Best of Category for the Achievement Award in the Next-Generation Emergency Medical Response through Data Analysis & Planning based on the substantial improvement my research models made in a real system. My 2012 paper in the management journal Interfaces reports the impact of this research observed in practice.
Since tenure, my research has focused on fire and EMS planning problems in tiered systems with multiple types of vehicles. There is not an analytical framework to support making decisions in tiered fire and EMS systems that send a mixture of vehicles to prioritized patients, and my research has focused on filling this important knowledge gap. My research group has formulated new MDP, integer programming, and approximate queueing models to study several important issues, such as how to cost-effectively route ambulances to patients with uncertain medical conditions, how to make joint deployment and routing decisions instead of assuming that these two interrelated decisions are separate, how to deploy a heterogeneous set of vehicles on a network for responding to prioritized calls for service, and how to design new risk-based response paradigms in congested networks. In this stream of research, I produced a suite of new models to support the design and operation of fire and EMS systems. My research group developed the first queueing model to evaluate the performance of fire departments when multiple vehicles respond to calls for service. This past year, this model was incorporated into the software used to route fire engines to calls in Canada.
My homeland security and infrastructure protection research dates to 2001. My early research was in the area of aviation security, where I developed and analyzed new integer programming and MDP models to assess the viability of risk-based prescreening systems. The common theme that pervades this research is the novel formulation and application of dynamic optimization models to capture and improve the operation of aviation security systems. The approach uses real-time assignment policies to adapt to variations in the day-to-day airport threat environment. My research provided policy insights regarding risk-based aviation security, served as the model for the TSA PreCheck paradigm, and provided the technical validation that helped facilitate its launch by the TSA. For my pivotal role in the creation and widespread adoption of risk-based aviation security strategies, my collaborators and I were awarded the INFORMS Impact Prize in 2018.
My research in this area took a new direction into cybersecurity after tenure. I recognized an opportunity to apply operations research methods to supply chain risk management (SCRM) to protect critical information technology infrastructure and enhance cybersecurity. My research group has formulated the first optimization models for enhancing SCRM by identifying a set of cybersecurity mitigations that are effective with respect to cost and risk-reduction and are robust to uncertainty. My research has introduced integer programming models to address security mitigation prioritization as well as a new exact algorithm for solving bi-level network interdiction models for critical infrastructure protection. My research group has also developed a new computational algorithm that efficiently solves a difficult class of infrastructure protection problems that considers the impact of adaptive adversaries, an important feature of the models in this area, on a network.
My disaster response and recovery research studies how to respond to emergencies on a network during and immediately after mass casualty incidents and how to restore a network after a disaster. This research area draws upon my emergency management and infrastructure protection expertise gained through the previous two areas of research. In this area of research, my group has investigated how community-driven data can be used to manage interdependent networks to enhance their recovery after a disruption. My research group has formulated and analyzed new models that study how to coordinate the activities of multiple types of service providers to restore a network after a disaster. The results provide insight into our understanding and management of infrastructure recovery from natural disasters.
My research formulates new operations research models and algorithms for solving important and interesting real-world problems of national interest and concern. I take this responsibility to serve my profession and our nation quite seriously. I believe that it is essential for researchers who are working on problems in the public sector to disseminate their research findings to the public through outreach in addition to dissemination in academic journals. Translating research concepts into practical messages is critical for influencing public policy and transitioning research concepts into practice. This is a common theme that permeates all my research activities.