Rate My Professor Saif Jabari

Saif Jabari serves as Associate Dean for Graduate Programs and Associate Professor of Civil and Urban Engineering in the Engineering division at New York University Abu Dhabi, holding a concurrent appointment as Global Network Associate Professor of Civil and Urban Engineering at NYU Tandon School of Engineering. He obtained his Bachelor of Science in Civil Engineering from the University of Jordan in 2001, Master of Science in Civil Engineering from the University of Minnesota Twin Cities in 2009, and Doctor of Philosophy in Civil Engineering from the same institution in 2012. Early in his career, Jabari worked as a Highway Engineer at Arabtech Jardaneh, Engineers and Architects, from 2002 to 2005. Following his doctoral studies, where he served as a research assistant from 2006 to 2012, he conducted postdoctoral research in the Mathematical Sciences and Analytics Department at the IBM T.J. Watson Research Center in Yorktown Heights, New York, from 2012 to 2014. He joined New York University Abu Dhabi as an Assistant Professor in 2014, advancing to his current roles.

Jabari's research specializes in the theoretical aspects of traffic flow, data analysis, modeling uncertainty, and emergent phenomena, with applications in traffic operations including traffic state estimation and prediction, distributed traffic control, and cybersecurity. His interests also include traffic flow theory, algorithms for urban network traffic management, applied probability, and statistical mechanics. He has earned the 2012 Milton Pikarsky Memorial Award for the best doctoral dissertation in science and technology from the Council of University Transportation Centers, the Best MS Thesis in Civil Engineering from the University of Minnesota in 2009, ITS Student of the Year in 2010 from the University of Minnesota ITS Institute, and an Award for Innovation and Outstanding Teaching from NYU Abu Dhabi Engineering. Key publications encompass "Nonlinear traffic prediction as a matrix completion problem with ensemble learning" (Transportation Science, 2022), "Stop and go: Exploring backdoor attacks in deep reinforcement learning-based traffic congestion control systems" (IEEE Transactions on Information Forensics and Security, 2021), "A real-time dispatching strategy for shared automated electric vehicles with performance guarantees" (Transportation Research Part E, 2021), "Sparse travel time estimation from streaming data" (Transportation Science, 2020), and "Traffic state estimation using stochastic Lagrangian dynamics" (Transportation Research Part B, 2018). In 2019, the Secretary General of the World Road Association praised his proposed traffic management plan adaptable to driverless vehicles.