The overarching mission of my research program is to better understand, assess, characterize, communicate, manage, and govern the risk of complex societal problems, from both theoretical and practical perspectives. I intend to accomplish this mission through a) the development of quantitative models examining systemic/stochastic impacts of various chronic/acute shocks on sociotechnical systems, b) the development of risk-informed decision models, and c) the investigation of cost-effective adaptation measures to advance the resilience and sustainability of our communities and critical infrastructure systems. The most significant research contributions have led to a better understanding of the complex nonlinear interactions of the socio-environmental stressors with CIS and communities through developments in algorithms and novel risk-informed decision frameworks. Three major research areas include:

This research area primarily focuses on the accurate modeling of critical infrastructure systems (CIS) vulnerability under incomplete information, energy demand prediction for efficient grid management under climate change, and modeling the complex interactions between the electricity distribution systems and natural hazards. Various categories of projects in this area include a) forecasting climate-sensitive energy demand for efficient grid management; b) modeling complex interactions between the energy systems and natural hazards; and c) assessing critical infrastructure systems vulnerability under incomplete information.

This research domain comprises problems that aim to understand how vulnerable populations are disproportionately impacted by extreme events and how to optimally allocate resources to minimize such effects. The three major categories of projects undertaken in this domain include: a) quantifying human behavior and social disparities under extreme events using large-scale human mobility data; b) investigating the effects of critical infrastructure failure on socially vulnerable communities; and c) understanding the causes of delayed post-disaster recovery of marginalized communities and how to minimize such challenges.

This research area focuses on developing novel data-centric frameworks that can accurately model health inequities, and social justice issues as complex non-linear functions of the socio-demographic, economic, and environmental factors. The various projects undertaken in this domain fall into two major categories: a) data-centric modeling of socio-environmental determinants of mental health; and b) assessing community safety and social justice issues.