个人信息：

冯朔，男，郑州大学计算机与人工智能学院副教授

香港城市大学 计算机科学 博士   2018.10 - 2021.10

英国纽卡斯尔大学 高级计算机科学 硕士 2012.9 - 2013.11

长安大学 计算机科学与技术 本科2007.9 - 2011.9

代表性项目：

国家重点研发计划工业软件专项《基于AI模型的产业链供应链网络协同关键技术及平台研发》项目子课题负责人

河南省《中原英才计划（引才系列）海外博士（博士后）》项目

某国内大型军工企业《XXX能力升级改进》项目

代表性论文：

[1] Feng, S., Keung, J., Yu, X., Xiao, Y., Bennin, K.E., Kabir, M.A., Zhang, M., 2020. COSTE: Complexity-based oversampling technique to alleviate the class imbalance problem in software defect prediction. Information and Software Technology.

[2] Feng, S., Keung, J., Yu, X., Xiao, Y., 2020. Investigation on the stability of SMOTE-based oversampling techniques in software defect prediction. Information and Software Technology.

[3] Feng, S., Keung, J., Yu, X., Xiao, Y., 2020. The impact of the distance on SMOTE-based oversampling techniques in software defect prediction. Information and Software Technology.

[4] Feng, S., Keung, J., Yu, X., Xiao, Y., 2021. Radius-based overlap cleaning technique to alleviate the class overlapping problem in software defect prediction. 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC).

[5] Yang, Z., Keung, J., Kabir, M. A., Yu, X., Tang, Y., Zhang, M., and Feng, S., 2020. AComNN: Attention enhanced Compound Neural Network for financial time-series forecasting with cross-regional features. Applied Soft Computing.

[6] Yu, X., Keung, J., Xiao, Y., Feng, S., Li, F., & Dai, H. 2022. Predicting the precise number of software defects: Are we there yet?. Information and Software Technology.

[7] Feng, S., Keung, J., Xiao, Y., Zhang, P., Yu, X., & Cao, X. (2024). Improving the undersampling technique by optimizing the termination condition for software defect prediction. Expert Systems with Applications, 235, 121084.

[8] Zhang, C., Shi, Z., Lu, W., Jin, Z., Feng, S*., & Xu, M. (2025). Proportional clustering-based undersampling for imbalanced data classification: C. Zhang et al. Knowledge and Information Systems, 67(12), 12299-12333.

学生培养

欢迎有学术志向、踏实努力的学生加入

联系方式

fengshuo@zzu.edu.cn