Sharon Di

Transportation digital twins have become increasingly popular tools to improve traffic efficiency and safety. However, the majority of effort nowadays is focused on the “eyes” of the digital twin, which is object detection using computer vision. I believe the key to empowering the intelligence of a transportation digital twin lies in its “brain,” namely, how to utilize the information extracted from various sensors to infer traffic dynamics evolution and devise optimal  control and management strategies with real-time feedback to guide the transportation ecosystem toward a social optimum. My current research interest lies in employing foundational models (such as Vision-Language Models (VLMs) and Large Language Models (LLM)) and GenAI (such as diffusion models), to create an urban transportation digital twin that simulates urban traffic scenarios and optimizes traffic management strategies. The applications range from pedestrian safety warning, adaptive traffic signal control, autonomous driving, to micromobility detection and tracking.

Biography:

Dr. Di is an Associate Professor in the Department of Civil Engineering and Engineering Mechanics at Columbia University in the City of New York. She also serves on the committee of Columbia's Center for Smart Cities in the Data Science Institute.

Dr. Di directs the DitecT (Data and innovative technology-driven Transportation) Lab, focusing on transportation systems. Her overarching research mission is to empower mobility for all, emphasizing the use of technology for social good. Specializing in mobility modeling and analytics, her research integrates sociotechnical solutions to deepen our understanding of human mobility and its complex interactions with other systems, in order to guide mobility toward resilience, sustainability, equity, and inclusivity.

Dr. Di’s research intersects transportation systems engineering and artificial intelligence (AI), encompassing game theory, data science, and optimization. She is currently focused on pioneering the development of digital twins for urban transportation management, leveraging cyber-physical systems technology. Within this framework, her research spans diverse areas, including autonomous vehicle control on shared roads with humans,  multi-modal mobility optimization, and the intersection of transportation with health considerations. Details about DitecT Lab and her research can be found here.

Dr. Di serves as the Associate Editor for journals including Transportation Science, Transportation Research Part B, and IEEE on ITS, and won the Transportation Science Meritorious Service Award from INFORMS in 2022. She received a number of awards including International Data Corporation’s Smart Cities North America Awards (2023), Best Paper Award from ACM SIGKDD Workshop on Urban Computing (2022), Amazon AWS Machine Learning Research Award (2020), NSF CAREER (2020), Transportation Data Analytics Contest Winner from Transportation Research Board (TRB) (2017), the Dafermos Best Paper Award Honorable Mention from the TRB Network Modeling Committee (2017), Chan Wui & Yunyin Rising Star Workshop Fellowship for Early Career Professionals from TRB (2014), Outstanding Presentation Award from INFORMS (2013), the Best Paper Award (2014) and Best Graduate Student Scholarship (2013) from Institute of Transportation Engineers (ITE). She was a participant in a long program on Mathematical Challenges and Opportunities for Autonomous Vehicles at the Institute for Pure & Applied Mathematics (IPAM) in UCLA in 2020. She has been a visiting research fellow at Bielefeld University’s Center for Interdisciplinary Research (ZiF) in Germany since 2021, and a visiting professor at Ecole Polytechnique in 2023-2024. Di received her PhD from University of Minnesota, Twin Cities, and served as a Postdoctoral Research Fellow at the University of Michigan Transportation Research Institute (UMTRI). 

Email:

Address:500 W 120th St #510, New York, New York, New York, United States, NY 10027