担任课程

本科：中级财务会计、会计管理信息系统

教育背景

2019年09月–2023年06月 暨南大学，财务管理，管理学博士

2015年08月–2018年03月  哈尔滨理工大学，会计学，管理学硕士

2011年09月–2015年07月 哈尔滨理工大学，会计学，管理学学士

工作经历

2023年12月–至今    海燕策略线路1

科研成果

论文：

[1] Di Wang, Zhanchi Wu, Junjie You, et al. Does hometown connection between chairmen and CEOs improve compensation–performance sensitivity in China?, Humanities and Social Sciences Communications, 2023, 10(1): 1-12.(SSCI Q1)

[2] Di Wang, Zhanchi Wu, Bangzhu Zhu. Controlling Shareholder Characteristics and Corporate Debt Default Risk: Evidence Based on Machine Learning, Emerging Markets Finance and Trade, 2022, 58(12): 3324-3339.(SSCI Q1)

[3] 王玉冬, 王迪, 王珊珊. 高新技术企业创新资金配置风险预警的FOA-SVM模型及实证, 系统工程理论与实践, 2018, 38(11): 2852-2862.(CSSCI)

[4] 王玉冬, 王迪（通讯作者）, 王珊珊. 基于PSO-BP和FOA-BP神经网络的财务危机预警模型比较, 统计与决策, 2018, 38(11): 177-179.(CSSCI)

项目：

2022年01月-2025年12月，参与，国家自然科学基金面上项目：“终极控制人特征与公司债务违约：作用机理与预警监控”（项目批准号 72173057）

2021年01月-2023年12月，参与，广东省自然科学基金面上项目：“终极控制人多元化投资：动因识别、风险传导与预警监控”（项目批准2021A1515011536）

联系方式

邮箱：willowdee2020@sina.com

Courses Taught

Bachelor: Intermediate Financial Accounting; Accounting Management Information System

Educational History

Jinan University    Guangzhou,China

Ph.D. in Management   Sep.2019-Jun.2023

Harbin University of Science and Technology Harbin,Heilongjiang,China

M.D. in Management  Aug.2015-Mar.2018

B.D. in Management  Sep.2011-Jul.2015

Work

Experience

Guangdong University of Foreign Studies   Guangzhou, China

Dec.2023 - Present

Research Outputs

[1]Di Wang, Zhanchi Wu, Junjie You, et al. Does hometown connection between chairmen and CEOs improve compensation–performance sensitivity in China?, Humanities and Social Sciences Communications, 2023, 10(1): 1-12.(SSCI Q1)

[2]Di Wang, Zhanchi Wu, Bangzhu Zhu. Controlling Shareholder Characteristics and Corporate Debt Default Risk: Evidence Based on Machine Learning, Emerging Markets Finance and Trade, 2022, 58(12): 3324-3339.(SSCI Q1)

[3]Wang Y D, Wang D, Wang S S. FOA-SVM model and empirical study on risk early warning of innovation fund allocation of high-tech enterprises[J]. Systems Engineering-Theory & Practice, 2018, 38(11): 2852-2862.(In Chinese, CSSCI)

[4]Wang Y D, Wang D, Wang S S.Comparison of financial crisis early warning models based on PSO-BP and FOA-BP neural networks, Statistics&Decision, 2018, 38(11): 177-179.(In Chinese, CSSCI)

Contact

E-mail：willowdee2020@sina.com