个人信息：

李可，教授，博导

西南财经大学统计与数据科学学院，数据科学系

电子邮箱：likec AT swufe.edu.cn

简历：

2013年8月于美国佛罗里达大学获得统计学博士学位，曾任职美国谷歌公司和瑞士诺华集团。2015年7月至今在西南财经大学工作，现为统计与数据科学学院教授、数据科学系主任。

代表性论文：

• Xu, L., Li, K., Wang, D., Zhou, F., Lv, F., Li, T., & Huang, Y. (2025+). Adaptive topological similarity learning for incomplete multi-view unsupervised feature selection. IEEE Transactions on Circuits and Systems for Video Technology, in press.

• Hao, X., Wang, Y., Li, K., Zhu, T., & Herasevich, V. (2025). Applying machine learning for perioperative adverse event prediction: a narrative review toward better clinical efficacy and usability. Anesthesiology and Perioperative Science, 3, 51.

• 顾雨熹, 王锦, 袁罡, 李可, & 陈晋莹 (2024). 棉花储藏过程中品质指标自然变异规律及影响因素研究. 中国纤检, 05, 98-108.

• Peng, X., Zhu, T., Chen, Q., Zhang, Y., Zhou, R., Li, K., & Hao, X. (2024). A simple machine learning model for the prediction of acute kidney injury following noncardiac surgery in geriatric patients: a prospective cohort study. BMC Geriatrics, 24, 549.

• Xiang, X. N., Wang, Z. Z., Zhang, J. Y., Li, K., Chen, Q. X., Xu, F. S., Zhang, Y. W., He, H. C., He, C. Q., & Zhu, S. Y. (2024). Telehealth-supported exercise/physical activity programs for knee osteoarthritis: a systematic review and meta-analysis. Journal of Medical Internet Research, 26, e54876.

• 姚潇, 李可, & 余乐安 (2022). 非平衡样本下基于生成对抗网络过抽样技术的公司债券违约风险预测研究. 系统工程理论与实践, 42, 2617-2634.

• Peng, X., Zhu, T., Wang, T., Wang, F., Li, K., & Hao, X. (2022). Machine learning prediction of postoperative major adverse cardiovascular events in geriatric patients: a prospective cohort study. BMC Anesthesiology, 22, 284.

• Chen, J., Liu, J., Qi, J., Gao, M., Cheng, S., Li, K., & Xu, C. (2022). City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017. Scientific Data, 9, 101.

• Chen, J., Li, Z., Song, M., Wang, Y., Wu, Y., & Li, K. (2022). Economic and intensity effects of coal consumption in China. Journal of Environmental Management, 301, 113912.

• Li, K., Zhou, F., Li, Z., Li, W., & Shen, F. (2021). A semi-parametric ensemble model for profit evaluation and investment decisions in online consumer loans with prepayments. Applied Soft Computing, 107, 107485.

• Li, K., Zhou, F., Li, Z., Yao, X., & Zhang, Y. (2021). Predicting loss given default using post-default information. Knowledge-Based Systems, 224, 107068.

• Li, Z., Hu, X., Li, K., Zhou, F., & Shen, F. (2020). Inferring the outcomes of rejected loans: An application of semisupervised clustering. Journal of the Royal Statistical Society: Series A, 183, 631-654.

• Shen, F., Zhao, X., Li, Z., Li, K., & Meng, Z. (2019). A novel ensemble classification model based on neural networks and a classifier optimisation technique for imbalanced credit risk evaluation. Physica A, 526, 101273.

• Chen, J., Fan, W., Li, K., Liu, X., & Song, M. (2019). Fitting Chinese cities' population distributions using remote sensing satellite data. Ecological Indicators, 98, 327-333.

• Li, Z., Li, K., Yao, X., & Wen, Q. (2019). Predicting prepayment and default risks of unsecured consumer loans in online lending. Emerging Markets Finance  & Trade, 55, 118-132.

• Chen, J., Xu, C., Li, K., & Song, M. (2018). A gravity model and exploratory spatial data analysis of prefecture-scale pollutant and CO2 emissions in China. Ecological Indicators, 90, 554-563.

• 吴茵茵, 李力, 李可, & 陈建东 (2018). 中国工业环境生产效率及环境保护税开征的研究. 中国人口·资源与环境, 28, 63-72.

• Tang, X., Li, K., & Malay, G. (2017). Bayesian multiple testing under sparsity for polynomial-tailed distributions. Statistica Sinica, 27, 1225-1242.

• Li, Z., Tian, Y., Li, K., Zhou, F., & Yang, W. (2017). Reject inference in credit scoring using semi-supervised support vector machines. Expert Systems with Applications, 74, 105-114.

• Tian, Y., Li, K., Yang, W., & Li, Z. (2017). A new effective branch-and-bound algorithm to the high order MIMO detection problem. Journal of Combinatorial Optimization, 33, 1395-1410.