Eren Erman Ozguven, Ph.D.
Eren Erman Ozguven is an Assistant Professor at the Department of Civil and Environmental Engineering at the FAMU-FSU College of Engineering. He received his Ph.D. degree from Rutgers University, Department of Civil and Environmental Engineering, with a concentration in Emergency Planning and Humanitarian Logistics. Following his graduation, he worked at Rutgers University Intelligent Transportation Systems (RITS) Lab as a Post-Doctoral Research Associate. He also has a M.S. degree in Industrial Engineering on Port Planning and Management from Bogazici University in Turkey.
Dr. Ozguven's research interests are focused on multi-modal emergency transportation operations, evaluation of roadway crashes, inventory control during emergency relief operations, simulation and modeling of transportation networks, and intelligent transportation systems. As a part of the Center for Accessibility and Safety for an Aging Population (ASAP), Dr. Ozguven's research program has evolved towards studying the accessibility and safety of the multi-modal transportation networks (both daily and emergency conditions) in order to assess the transportation needs of the vulnerable populations such as aging.
One of his recent publications, which has been accepted for publication in Transport Reviews, presents a review of the aging population-focused emergency literature utilizing a knowledge base development methodology supported with a GIS-based case study application set in Florida. Importance is given to both ensuring the resiliency of the transportation infrastructure and meeting the needs of aging populations in this paper. As a result of this metadata-based analysis, critical research needs and challenges are identified with planning recommendations.
Dr. Ozguven also works on developing novel methodologies to analyze the spatial and temporal patterns of aging people-involved accidents, measure the aging population-focused accessibility to multi-modal facilities, and to extensively evaluate the existing travel time/traffic data and aging people driving patterns with a focus on exploring ways to fuse these two separate data sets. Previously, Dr. Ozguven proposed a novel RFID-based online emergency management framework that can be effectively used to synchronize critical delivery and consumption processes, to facilitate sustainable resource tracking, and to provide an efficient distribution of flow in support of disaster relief efforts. As a result, he developed an efficient mathematical model utilizing both an offline inventory planning strategy and online control theoretical methodologies that can be integrated with the help of RFID technologies as the main resource-tracking tool. This model could potentially be used in federal and state emergency plans and mechanisms during the disaster relief period. He has published two papers in Transportation Research Part C based on this research.
Dr. Ozguven was actively involved in several externally funded emergency evacuation and planning projects that were successfully completed by Rutgers University Intelligent Transportation Systems (RITS) Lab. Before joining the FAMU-FSU School of Engineering, he has been leading the effort for the preparation of the Movement Controller Tool framework for the NY-NJ-CT-PA Combined Statistical Area (CSA) Region. This involved an extensive analysis of the regional transportation network with the available truck routes, and determining the data and technical requirements of creating a tool that will facilitate the transportation of vital supplies between different origins and destinations within the Region optimally.
Dr. Ozguven has authored 15 journal papers and 21 international conference proceedings. He has been a referee for Transportation Research Part A, Transportation Research Part C, Transportation Research Part D, Transportation Research Part E, European Journal of Operational Research, Transport Policy, Transportation Research Board, IEEE Transactions on ITS, OMEGA: The International Journal of Management Science, and IEEE Conference on Intelligent Transportation Systems.