DIGITAL TWIN
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DIGITAL TWIN
Digital Twins @ C2SMARTER Center
New York University
KAAN OZBAY
DIRECTOR, C2SMART PROFESSOR, NYU
Kaan M.A. Özbay joined Department of Civil and Urban Engineering and Center for Urban Science and Progress (CUSP) at NYU in August 2013. Since 2017, Professor Ozbay has been the Founding Director of the C2SMART Center (Tier 1 UTC funded by USDOT). He is also Global Network Professor of Civil and Urban Engineering, NYU Abu Dhabi (NYUAD) and Global Network Professor of Engineering and Computer Science, NYU Shanghai (NYUSH). Professor Ozbay was a tenured full Professor at the Rutgers University Department of Civil and Environmental Engineering. He joined Rutgers University as a tenure track Assistant Professor in July, 1996. In 2008, he was a visiting scholar at the Operations Research and Financial Engineering (ORFE) Department of Princeton University.
Dr. Ozbay is the recipient of the prestigious National Science Foundation (NSF) CAREER award. Dr. Ozbay is the co-editor of an edited book titled “Dynamic Traffic Control & Guidance” published by Springer Verlag’s “Complex Social, Economic and Engineered Networks” series in 2013. In addition to this book, Dr. Ozbay is the co-author of three other books titled “Feedback Based Ramp Metering for Intelligent Transportation Systems” published by Kluwer Academics in 2004, “Feedback Control Theory for Dynamic Traffic Assignment”, Springer-Verlag and “Incident Management for Intelligent Transportation Systems” published by Artech House publishers both in 1999.
Dr. Ozbay published approximately 425 refereed papers in scholarly journals and conference proceedings. Professor Ozbay serves as the “Associate Editor” of Networks and Spatial Economic journal and Transportmetrica B: Transportation Dynamics journal. He is a member of the editorial board of the ITS journal.
Professor Ozbay served as the elected member of Board of Directors of the Intelligent Transportation Society of New Jersey in 2013. He has been an active member of national and international scientific and professional committees and organizations, including IEEE, ITE, ASCE, AASHTO and the Transportation Research Board (TRB) of the US National Academies. He also served as a member of the Board of Directors of the University Transportation Research Center (UTRC) at the City University of New York – USDOT’s Region 2 University Transportation Center.
Since 1994, Dr. Ozbay, has been the Principal Investigator and Co-Principal Investigator of 120 projects funded at a level of more than $30,00,000 by National Science Foundation, NJDOT, NYMTC, NY State DOT, New Jersey Highway Authority, USDOT, FHWA, VDOT, CUNY University Transportation Research Center (UTRC), Department of Homeland Security, USDOT ITS Research Center of Excellence. He was the founding director of the Rutgers Intelligent Transportation Systems (RITS) laboratory.
Research Interests: Development of simulation models of large scale complex transportation systems, advanced technology and sensing applications for Intelligent Transportation Systems, modeling and evaluation of traffic incident and emergency management systems, feedback based on-line real-time traffic control techniques, traffic safety, application of operations research techniques in network optimization and humanitarian inventory control, and transportation economics.
JOSEPH CHOW
DEPUTY DIRECTOR, C2SMART, PROFESSOR, NYU
Dr. Joseph Chow is an Institute Associate Professor in the Department of Civil & Urban Engineering and the Deputy Director at the C2SMART Tier-1 University Transportation Center at NYU, and heads BUILT@NYU: the Behavioral Urban Informatics, Logistics, and Transport Laboratory. His research expertise lies in transportation systems, with emphasis on multimodal networks, behavioral urban logistics, smart cities, and transport economics. He is an NSF CAREER award recipient; he is a former elected Chair of the Urban Transportation SIG and appointed TSL Cluster Chair at INFORMS Transportation Science & Logistics Society, chair of the TRB subcommittee on Route Choice and Spatiotemporal Behavior, and is an appointed Associate Editor for International Journal of Transportation Science & Technology and Transportation Research Record, the journal for the Transportation Research Board of the National Academies.
At NYU he is an Associated Faculty at CUSP and Rudin Center. Prior to NYU, Dr. Chow was the Canada Research Chair in Transportation Systems Engineering at Ryerson University. From 2010 to 2012, he was a Lecturer at University of Southern California and a Postdoctoral Scholar at UC Irvine. He obtained a Ph.D. in Transportation Engineering from UC Irvine (‘10), and an M.Eng. (‘01) and B.S. (‘00) in Civil Engineering from Cornell University with a minor in Applied Math. Dr. Chow is a former Eisenhower and Eno Fellow and a licensed PE in NY.
EUGENE VINITSKY
ASSISTANT PROFESSOR, NYU
Eugene Vinitsky is an incoming Assistant Professor at NYU Tandon in 2023 based in Civil Engineering, and currently a PhD candidate in controls and optimization at UC Berkeley in Mechanical Engineering. Prior to that, he received his MS in physics from UC Santa Barbara and a BS in physics from Caltech. At UC Berkeley, he focuses on scaling multi-agent reinforcement learning to tackle the challenges associated with transportation system optimization. As a member of the CIRCLES consortium, he is responsible for the reinforcement learning algorithms and simulators used to train and deploy energy-smoothing cruise controllers onto Tennessee highways. He is currently a visiting researcher in reinforcement learning at Facebook AI and has interned at Tesla Autopilot and at the Multi-Agent Artificial Intelligence Team at DeepMind. His research has been published at ML venues such as CORL, neurIPS, and ICRA and at transportation venues such as ITSC. He is the recipient of the NSF Graduate Student Research Award, a two time recipient of the Dwight David Eisenhower Transportation Fellowship, and received an ITS Outstanding Graduate Student award. He is one of the primary developers of Flow, a library for benchmarking and training autonomous vehicle controllers.
His research goal is to see complex, human-like behavior emerge from unsupervised interaction between groups of learning agents with an applications focus on enabling autonomous vehicles to operate in rich scenarios. Concretely this leads to a lot of questions his research pursues:
How can we use RL to design models of human agents?
- How can we ensure that RL designed agents are human-compatible?
- How can we synthesize environments that push and test the capabilities of our agents?
- What algorithmic advances and software tools are needed to address these questions?
- In practice this means working on understanding how to push the state of the art in multi-agent RL algorithms, designing new data-driven simulators, and trying to deploy simulator-designed controllers into real-world systems.
ZILIN BIAN
RESEARCHER, NYU
Zilin is a Research Associate at New York University, where he focuses on transportation planning and engineering. He holds a Ph.D. in Transportation Planning and Engineering from NYU, as well as a master's degree from the University of Florida.
Zilin's research interests lie at the intersection of urban decision science and artificial intelligence, with a particular emphasis on traffic incident management, transportation operation and planning analysis, and transportation policy. His work involves developing and applying advanced artificial intelligence techniques as well as digital twins intelligence, with the goal of improving mobility, safety, and accessibility for all.
In addition to his research, Zilin is also passionate about teaching and mentoring the next generation of transportation professionals. He has served as a teaching assistant for several transportation courses at NYU, and enjoys sharing his knowledge and experience with students from a variety of backgrounds.
Overall, Zilin is a dedicated researcher and educator who is committed to advancing the field of transportation through innovative research and collaboration.
JINGQIN GAO
ASSISTANT DIRECTOR, C2SMARTER, NYU
Dr. Jingqin Gao is a dedicated professional with over 10 years of experience in transportation planning and engineering. She has served as principal investigator (PI), co-PI, and lead researcher for multiple projects funded by the U.S. DOT, NASEM, AASHTO, NYSDOT, NYCDOT, and NJDOT. As the Assistant Director of Research at C2SMART University Transportation Center funded by the U.S. Department of Transportation (USDOT). Dr. Gao assisted the center to secure a $15M grant, including $10M from U.S. DOT, to pursue a research and educational program focused on understanding and combatting traffic congestion. Dr. Gao’s research has focused on emerging technologies and urban analytics for smart transportation. She is best known for her research on evaluating the field performance of U.S. DOT Connected Vehicle Pilot Deployment Safety Applications in New York City, utilizing cooperative automated transportation data for transportation operational strategies, assessing the mobility and policy impacts on transportation systems during COVID-19, AI-based transportation solutions for smart cities, and double parking analysis.
Before joining NYU, Dr. Gao worked in the Modeling and Data Analysis unit at the New York City Department of Transportation (NYCDOT), which supports the agency’s internal planning, technical review processes, and coordinated with external agencies on regional projects.
Beyond her academic pursuits, she champions women in STEM, diversity, equity, and workforce development. Dr. Gao is named as Who’s Who America in Professional Women in 2023 and is a recipient of the Dr. Louis J. Pignataro Memorial Transportation Education Award by ITE MET section and National Leadership Legacy Award from the WTS-GNY chapter.
FAN ZUO
RESEARCHER, NYU
Dr. Fan Zuo is an accomplished Transportation Engineer with a Ph.D. from New York University and a B.S. from Chongqing University, China. Specializing in the intersection of artificial intelligence and transportation, his expertise includes learning theory, human behavior, interactive simulation, and Intelligent Transportation Systems (ITS), with a strong foundation in machine learning, particularly computer vision. Dr. Zuo is skilled in utilizing tools like SUMO and Carla for transportation solutions and has contributed significantly to the fields of connected vehicle safety, smart city solutions, and the analysis of COVID-19's impact on mobility. He has co-authored several influential papers on Connected and Autonomous Vehicles (CAV) and emerging transportation technologies.