SRIBD Research Scientist
Time series, Econometric modeling, Machine learning
Ph.D. in The Chinese University of Hong Kong
Bachelor’s degree in University of Science and Technology of China
Overseas High-Caliber Personnel, Shenzhen
Overseas Research Award In The Chinese University of Hong Kong
Outstanding Graduate In University of Science and Technology of China
Dr. Shan Dai is currently a research scientist in Shenzhen Research Institute of Big Data. His main research interests include time series, econometric modeling and machine learning related theory and practice. He received a Bachelor's degree in Science from University of Science and Technology of China, a Ph.D. degree in Statistics from The Chinese University of Hong Kong. He was also recognized as an Overseas High-Caliber Personnel (Shenzhen). He has published several peer-reviewed papers on statistical journals and machine learning conferences including Journal of Time Series Analysis and Proceedings of the Winter Simulation Conference, and got several patents granted and accepted. Dai is currently the PI of a Shenzhen Excellent Science and Technology Innovation Talents Cultivation Project (PhD Start-Up).
SELECTED PUBLICATIONS (*denotes corresponding author)
- Dai, S. and Chan, N.H.* (2023). Testing of Constant Parameters for Semi-Parametric Functional Coefficient Models with Integrated Covariates. J. Time Ser. Anal., 44: 474-486.
- Zhang, M., Liu, G., Dai, S.*, He, Y. (2023). Input Uncertainty Quantification Via Simulation Bootstrapping. Proceedings of the 2023 Winter Simulation Conference (WSC). Accepted.