Hiba Baroud, Ph.D.
Hiba Baroud is an associate professor and the associate chair in the Department of Civil and Environmental Engineering at Vanderbilt University. She holds secondary appointments in Computer Science and Earth and Environmental Science. Hiba is currently the interim director of the Vanderbilt Center for Sustainability, Energy, and Climate.
Her research is at the intersection of data analytics and risk and resilience modeling. Her group develops and applies methods founded in statistical learning, network models, and decision analysis to evaluate infrastructure performance during disasters. She is particularly interested in uncertain and dynamic interdependencies across multiple systems (infrastructure, humans, environment). Applications are focused on smart cities, developing countries, and Arctic communities.
She is the co-chair of the Risk and Resilience Measurements Committee of the Infrastructure Resilience Division in the American Society of Civil Engineers (ASCE). She serves as Associate Editor of the ASCE Natural Hazards Review.
Hiba is the recipient of the 2019 Global Voices Fellowship, the 2020 National Science Foundation Early CAREER award, and the 2022 National Academy of Sciences Arab-American Frontiers Fellowship. She was selected as a member of the Global Young Academy in 2023 and named a Fellow of the International Science Council in 2024.
Research Areas
Critical Infrastructures Modeling
Critical infrastructures constitute key elements in the operation of today’s society and economy. The Department of Homeland Security identifies 16 sectors such as transportation, energy, and water systems, among others. Some of the major concerns pertaining to such systems are security, resilience, and sustainability. A number of factors including natural hazards, extreme weather, climate change, intelligent threats, aging infrastructure, and restrictive funding make critical infrastructures management challenging. As a result, research is currently focused on identifying and developing tools that address such issues as well as define and measure the risk, reliability, and resilience in critical infrastructure systems. The objective of this research area is to provide an efficient risk-informed decision making process for the protection of civil infrastructures.
Interdependent Systems Data Analytics
Critical infrastructure systems are highly correlated and interdependent systems. A disruptive event impacting one system not only results in cascading effects in the physically disrupted system but can also have indirect impacts on interdependent systems. For instance, a disruption in the water infrastructure will result in failures in communications, power, and transportation systems leading to large scale impacts on the nation’s economy. With the recent technological advances, systems information is recorded on a timely basis. As a result, questions arise with respect to managing high volume and high velocity data collected from a variety of sources, or in other words Big Data. The challenge in this area is to develop or identify the appropriate statistical techniques to draw inferences, make predictions, and inform decision making to improve preparedness and recovery investment strategies.