Dingyi Zhuang (庄丁奕)

dingyi [AT] mit [DOT] edu

I am a final-year Ph.D. candidate in Transportation at MIT JTL Transit Lab, supervised by Prof. Jinhua Zhao and also a member of UrbanAI Lab. I earned my M.Eng (2021) at McGill University under Prof. Lijun Sun and my B.Sc. (2019) in Mechanical Engineering from Shanghai Jiao Tong University advised by Prof. Jiangang Jin. I also served as a research assistant at the National University of Singapore with Prof. Lee Der-Horng.

I bring AI&ML techniques to transportation engineering and urban planning, broadly including four key research themes. (1) Spatiotemporal data modeling leverages graph neural networks for imputation, forecasting, and (dynamic) kriging across large-scale urban systems. (2) Uncertainty quantification focuses on frequentist approaches to ensure reliable and trustworthy prediction intervals in real-world deployments. (3) Intelligent transportation systems addresses multi-agent control, equity, and bias mitigation, promoting fair, human-centered mobility. (4) Generative AI integrates unstructured data—from images to textual content—to enhance spatial reasoning and planning capability of foundation models in urban scenarios.

I spent time doing research at Bosch Center for Artificial Intelligence, Morgan Stanley Machine Learning Research Team, and Singapore-MIT Alliance for Research and Technology (SMART).

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