Dr. Ali Shamshiripour received his Ph.D. in Civil (Transportation) Engineering from the University of Illinois at Chicago. Upon graduation, he moved to the Massachusetts Institute of Technology as a Research Scientist under the supervision of Prof. Moshe Ben-Akiva, where he co-supervised multiple master's and Ph.D. students in the departments of Civil and Environmental Engineering and Electrical Engineering and Computer Science. He is currently an Assistant Professor at the Department of Civil & Architectural Engineering & Mechanics at the University of Arizona (UA). At the UA, he established the Urban Ecosystems Lab (UE Lab) and joined the Center for Applied Transportation Sciences (CATS) as an Assistant Director.
Dr. Shamshiripour's research spans the intersections between transportation engineering, urban policy, and computer science. The results of his research have been disseminated via 17 peer-reviewed publications in high-impact journals (including in Transportation Research Parts A, C, D, and F), 35 conference presentations, and various webinars, guest lectures, and media coverages. His research encompasses three inter-dependent streams:
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Analysis and modeling of human activity-travel behavior and behavioral dynamics in different time scales, ranging from short- to long-term planning and habitual developments to within-day actions.
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Studying and designing a wide range of novel mobility solutions that promise to improve individual- to system-level benefits, including welfare, well-being, and sustainability.
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Developing state-of-the-art agent- and activity-based simulation platforms for full-scale, comprehensive evaluations of the impacts of different smart mobility solutions (Urban Air Mobility, Mobility as a Service, and Automated Mobility), tolling or congestion pricing scenarios, etc.
In addition to his research endeavors, Dr. Shamshiripour has been actively committing to various acts of service throughout his career, including co-organizing multiple webinars hosted by TRB’s Standing Committee on Economic Development and Land Use (AMS50).
The Urban Ecosystems Lab (UE Lab), founded and led by Dr. Ali Shamshiripour, strives to research pathways to synergistically foster environmental sustainability, economic prosperity, etc., in future cities. The UE Lab recognizes that a synergistic realization of these potentials lies in cross-cutting collaborations across various disciplines, including, but not limited to, civil engineering, environmental engineering, electrical engineering, computer science, and urban planning and policy. Therefore, the Lab is keen to collaborate with peer research groups of scholars from other disciplines.
The UE Lab also recognizes its members as its most important asset and strives to empower them in their professional development journey according to their own preferences. The Lab is dedicated to building a growing family of diverse researchers that: (a) help each other grow and (b) pull their expertise to pursue their common goal, i.e., building a better future.
The UE Lab was founded on August 14, 2023, and recruits two fully-funded Ph.D. students! Are you interested in joining?
"The Center for Applied Transportation Sciences (CATS) is a research, training, and capacity-building resource for regional governments, educational institutions, and private companies. The center focuses on smart cities, particularly in the areas of transportation systems management and operations and mobility on demand. Yao-Jan Wu, associate professor of civil and architectural engineering and mechanics, directs the center, including core and affiliated faculty members; and academic, industry, and agency partners, all working together to improve local, regional, and national transportation systems.
The mission of CATS is to serve as a research, training, and capacity-building resource for regional governments, educational institutions, and private sectors in the field of Smart Cities with emphasis on Transportation Systems Management and Operations (TSMO) and Mobility on Demand (MOD)." [CATS Website, Aug 18, 2023]
