Zhang Huanhuan

Email: hhzhang6@swufe.edu.cn

He graduated with a Ph.D. in Management Science and Engineering from the University of Electronic Science and Technology of China. After graduation, he taught at Southwestern University of Finance and Economics. From 2017 to 2018, he was a visiting scholar at the Department of Computer Science and Artificial Intelligence of the University of Granada in Spain for one year. His main research directions are intelligent decision analysis and data mining, and he has published academic papers in many important journals in the field of management science. He has won the second prize of Jiangsu Province Philosophy and Social Science Outstanding Achievement Award, the third prize of Sichuan Province Social Science Outstanding Achievement Award, and other awards. He has participated in many National Natural Science Foundation projects as a research backbone.

Main Scientific Research Achievements

[1] Zhang, H., Kou, G., & Peng, Y. (2021). Large-scale peer-to-peer loan consensus based on minimum cost consensus. Journal of the Operational Research Society, 1-12.

[2] Zhang, H., Kou, G., & Peng, Y. (2019). Soft consensus cost models for group decision making and economic interpretations. European Journal of Operational Research, 277(3), 964-980. (ESI hot paper, highly cited paper)

[3] Gong, Z., Zhang, H., Forrest, J., Li, L., & Xu, X. (2015). Two consensus models based on the minimum cost and maximum return regarding either all individuals or one individual. European Journal of Operational Research, 240(1), 183-192.

[4] Gong, Z., Xu, X., Zhang, H., Ozturk, UA, Herrera- Viedma, E., & Xu, C. (2015). The consensus models with interval preference opinions and their economic interpretation. Omega, 55, 81-90.

[5] Gong, Z., Zhang, H., Xu, C., & Xu, X. (2015). Consensus models at minimum quadratic cost and its economic interpretation. IEEE International Conference on Gray Systems and Intelligent Services, 339- 345.

[6] Gong, Z., Zhang, H., Guo, C., Xu, X., & Xu, C. (2014). Two consensus models based on the minimum cost and the maximum return. IEEE International Conference on Fuzzy Systems, 1-4.