Zhicheng Liu

Ph.D. / Postdoc

Zhicheng Liu received his Ph.D. degree from School of Information Science and Engineering, Southeast University, China, 2021. From Nov. 2018 to Oct. 2019, he was a visiting Ph.D. student at Tandon School of Engineering, New York University. During his Ph.D. studies, he focused on data-driven urban planning, aiming at developing machine learning models to answer what-if questions in urban planning and assist urban planners in decision making. His general research area is on urban computing i.e. using machine learning techniques, e.g., probabilistic modeling and graph representation learning, to address urban problems, e.g., transportation and real estate.

Research Interests

Urban Computing
Spatiotemporal Data Mining
Graph Representation Learning
Intelligent Transportation Systems

Selected Publications

Liu, Z., Cao, J., Xie, R., Yang, J., & Wang, Q. (2020). Modeling Submarket Effect for Real Estate Hedonic Valuation: A Probabilistic Approach. IEEE Transactions on Knowledge and Data Engineering.
Liu, Z., Miranda, F., Xiong, W., Yang, J., Wang, Q., & Silva, C. (2020, April). Learning geo-contextual embeddings for commuting flow prediction. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 01, pp. 808-816).
Liu, Z., Yan, S., Cao, J., Jin, T., Tang, J., Yang, J., & Wang, Q. (2018, December). A bayesian approach to residential property valuation based on built environment and house characteristics. In 2018 ieee international conference on big data (big data) (pp. 1455-1464). IEEE.