BIMSA > 高瑞泽
助理研究员 高瑞泽

团队: 数字经济

办公室: A11-101

邮箱: gaoruize@bimsa.cn

研究方向: 金融科技、量化投资、商务智能分析、数据资产研究

CV

个人简介

Ruize Gao is an assistant professor at Beijing Institute of Mathematical Sciences and Applications. His research interests include digital economy and data mining. He has published in leading journals such as Decision Support Systems, Information Sciences, Knowledge-based Systems, Financial Innovation, Expert Systems with Applications, Technology in Society, International Journal of Accounting Information Systems. He hosts one funding project under the China Postdoctoral Science Foundation.

教育经历

  • 2017 - 2023      Chongqing University      Management Science and Engineering      博士
  • 2013 - 2017      Chongqing University      Information Management and Information Systems      学士

工作经历

  • 2025 -      BIMSA      助理研究员
  • 2023 - 2025      Tsinghua University & BIMSA      博士后

出版物

  • [1] Shaoze Cui, Ruize Gao, Junwei Kuang, Liang Yang, Huaxin Qiu, Xiaowen Wei, An interpretable imbalance ensemble classification method for readmission risk assessment incorporating multi-view perturbation and SHAP analysis, Decision Support Systems, 190, 114404 (2025)
  • [2] Ruize Gao, Shaoze Cui, Yu Wang, Wei Xu, Predicting financial distress in high-dimensional imbalanced datasets: A multi-heterogeneous self-paced ensemble learning framework, Financial Innovation (2025)
  • [3] Ying Zhou, Zhi Xiao, Ruize Gao, and Chang Wang, Using data-driven methods to detect financial statement fraud in the real scenario, International Journal of Accounting Information Systems, 54(2024), 100693
  • [4] Yuelong Zheng; Bingjie Zhou; Chen Hao; Ruize Gao; Mengya Li, Evolutionary game analysis on the cross-organizational cooperative R&D strategy of general purpose technologies under two-way collaboration, Technology in Society, 76(2024), 102473
  • [5] Ruize Gao, Shaoze Cui, Hongshan Xiao, Weiguo Fan, Hongwu Zhang, and Yu Wang, Integrating the sentiments of multiple news providers for stock market index movement prediction: A deep learning approach based on evidential reasoning rule, Information Sciences, 615(2022), 529-556
  • [6] Ruize Gao, Xin Zhang, Hongwu Zhang, Quanwu Zhao, and Yu Wang, Forecasting the overnight return direction of stock market index combining global market indices: A multiple-branch deep learning approach, Expert Systems With Applications, 194(2022), 116506
  • [7] Xin Zhang, Hongshan Xiao, Ruize Gao, Hongwu Zhang, and Yu Wang, K-nearest neighbors rule combining prototype selection and local feature weighting for classification, Knowledge-Based Systems, 243(2022), 108451
  • [8] R Sui, R Gao, J Li, Consumer Data Collection and Pricing for Two-sided Market Platforms, SSRN (2023)
  • [9] R Gao, Q Zhao, Y Wang, Z Hua, Digitalization of technology advisory service demand for crowdsourcing service provider selection, 第十六届 (2021) 中国管理学年会论文集 (2021)
  • [10] X Zhang, H Xiao, R Gao, Y Wang, Z Hua, Data Reduction based on Prototype Selection and Local Feature Weighting in K Nearest Neighbor rule, 第十六届 (2021) 中国管理学年会论文集 (2021)
  • [11] R Sui, R Gao, J Li, Optimal Data Pricing Decisions of Competitive Two-Sided Platforms with Heterogeneous Data Costs, SSRN

 

更新时间: 2025-07-25 11:00:07