Dingyi Zhuang

M.Eng.

Dingyi Zhuang joined the smart transport group as a master student in September 2019 and is estimated to graduate in August 2021. He received his Bachelor’s degree in Mechanical Engineering at Shanghai Jiao Tong University and was a research student at National University of Singapore. His supervisors in two universities are Prof. Jiangang Jin and Prof. Lee Der-Horng respectively. His research interests lie in spatial-temporal data mining and urban computing. Three particular questions are (1) how to adapt advanced graph network methods on transportation system, especially to infer/forecast the states/values of unseen nodes in the network (2) how to utilize interpretability of probabilistic factorization models on mobility modeling (3) how physical traffic flow models can be integrated with (differentiable) deep learning.

Research Interests

Urban computing & smart city
Graph neural network & complex network
Spatio-temporal data mining
Bayesian probabilistic factorization models
Reinforcement learning based traffic control

Selected Publications

Zhuang D, Hao S, Lee D H, et al. From compound word to metropolitan station: Semantic similarity analysis using smart card data[J]. Transportation Research Part C: Emerging Technologies, 2020, 114: 322-337.
Zhuang D, Jin J G, Shen Y, et al. Understanding the bike sharing travel demand and cycle lane network: The case of Shanghai[J]. International Journal of Sustainable Transportation, 2020, 15(2): 111-123.
Wu Y, Zhuang D, Labbe A, et al. Inductive graph neural networks for spatiotemporal kriging[J]. In Proceedings of the AAAI Conference on Artificial Intelligence