I am a postdoctoral researcher in the Department of Economics at Turku School of Economics, University of Turku. My research interests lie at the intersection of efficiency and productivity analysis, machine learning, and nonparametric econometrics and their applications to energy, resources, and environmental fields.
I received a Ph.D. in Economics and Business Administration from Aalto University School of Business under the supervision of Prof. Timo Kuosmanen. Before joining Aalto University BIZ, I earned my MSc. in Management Science from China University of Geosciences.
Here you’ll find links to my publications and my CV. Feel free to contact me at sheng.dai [at] utu.fi.
Dai, S. 2023. Variable selection in convex quantile regression: L1-norm or L0-norm regularization? European Journal of Operational Research, 305, 338-355.
Dai, S., Kuosmanen, T. & Zhou, X. 2023. Generalized quantile and expectile properties for shape constrained nonparametric estimation. European Journal of Operational Research, 310, 914-927.
Liao, Z., Dai, S.*, & Kuosmanen T. 2023. Convex Support Vector Regression. European Journal of Operational Research, In Press.
Cheng, J., Yi, J., Dai, S. & Xiong, Y. 2019. Can low-carbon city construction facilitate green growth? Evidence from China’s pilot low-carbon city initiative. Journal of Cleaner Production, 231, 1158-1170. [ESI top 1%; Highly cited paper]
pyStoNED: A Python package for convex regression and frontier estimation