Zhaonan Wang (王肇南)

Zhaonan Wang is an Assistant Professor at NYU Shanghai and an associated faculty member with CUSP (Center for Urban Science + Progress) at NYU Tandon. He has an interdisciplinary background in geospatial, AI, and urban science, with an overarching research goal to understand network dynamics of cities and support decision making with intricate real-world data. His research works have been published on top-tier AI and data science venues, including AAAI, KDD, WWW, ICDE. Before joining NYU Shanghai, Zhaonan was a postdoctoral researcher at University of Illinois Urbana-Champaign and NSF I-GUIDE. He obtained his PhD in 2022 at the University of Tokyo, where he was awarded MEXT Scholar by Japanese Government, and received best resource paper runner-up at ACM CIKM 2021. Zhaonan was one of 37 nominees who were admitted to Peking University with College Entrance Exam (“Gaokao”) exempted in Beijing 2010. He’s recently been awarded by Shanghai municipality and Alibaba DAMO Academy for his research achievements. 

Select Publications

• Z Wang, R Jiang, H Xue, FD Salim, X Song, R Shibasaki, W Hu, S Wang. 2024. Learning Spatio-Temporal Dynamics on Mobility Networks for Adaptation to Open-World Events. Artificial Intelligence, 104120.
• R Jiang*, Z Wang*, J Yong, P Jeph, Q Chen, Y Kobayashi, X Song, S Fukushima, T Suzumura. 2023. Spatio-Temporal Meta-Graph Learning for Traffic Forecasting. Proceedings of the AAAI conference on Artificial Intelligence 37 (7), 8078-8086.
• R Jiang*, Z Wang*, Y Tao, C Yang, X Song, R Shibasaki, SC Chen, ML Shyu. 2023. Learning Social Meta-Knowledge for Nowcasting Human Mobility in Disaster. Proceedings of the ACM Web Conference 2023, 2655-2665.
• Z Wang, R Jiang, H Xue, FD Salim, X Song, R Shibasaki. 2022. Event-Aware Multimodal Mobility Nowcasting. Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4228-4236.
• Z Wang, T Xia, R Jiang, X Liu, KS Kim, X Song, R Shibasaki. 2021. Forecasting Ambulance Demand with Profiled Human Mobility via Heterogeneous Multi-Graph Neural Networks. 2021 IEEE 37th International Conference on Data Engineering (ICDE), 1751-1762.