最终学位：博士
导师类型：
电子邮箱：cqq@sxu.edu.cn
联系电话：0351-7010566
研究方向：数据挖掘
陈庆强，博士，讲师，2024年博士毕业于山西大学计算机与信息技术学院，研究兴趣主要包括机器学习和数据挖掘，重点围绕贝叶斯错误率估计、模型泛化性能提升、实例选择、标签噪声学习等问题开展学术研究，以第一作者或通讯作者在《IEEE Transactions on Pattern Analysis and Machine Intelligence》、《IEEE Transactions on Knowledge and Data Engineering》、《Pattern Recognition》、《清华大学学报》、AAAI等国内外期刊和会议发表论文多篇。曾获第五届中国“互联网+”大学生创新创业大赛银奖和第三届CCF优秀大学生学术秀（博士组）二等奖。担任IEEE TKDE、IEEE TNNLS、EAAI、ICML、AAAI等期刊和会议的审稿人。
[1] Qingqiang Chen, Fuyuan Cao, Ying Xing, Jiye Liang. Evaluating Classification Model Against Bayes Error Rate. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(8): 9639-9653. (CCF A类期刊)
[2] Fuyuan Cao, Qingqiang Chen*, Ying Xing, Jiye Liang. Efficient Classification by Removing Bayesian Confusing Samples. IEEE Transactions on Knowledge and Data Engineering, 2024, 36(3): 1084-1098. (CCF A类期刊)
[3] Qingqiang Chen, Fuyuan Cao, Ying Xing, Jiye Liang. Instance Selection: A Bayesian Decision Theory Perspective. In Proceedings of the AAAI Conference on Artificial Intelligence, 2022, 36(6): 6287-6294. (CCF A类会议)
[4] Qingqiang Chen, Gaoxia Jiang, Fuyuan Cao, Changqian Men, Wenjian Wang. A General Elevating Framework for Label Noise Filters. Pattern Recognition, 2024, 147: 110072. (CCF B类期刊)
[5] Qingqiang Chen, Wenjian Wang, Gaoxia Jiang. Label Noise Filtering Based on the Data Distribution. Journal of Tsinghua University (Science and Technology), 2019, 59(4): 262-269. (EI收录)
[1] 科技创新2030-“新一代人工智能”重大项目(No.2020AAA0106100): 认知计算基础理论与方法研究, 2020.11-2024.10, (参与)
[2] 国家自然科学基金项目(No.62376145): 因果表征的聚类算法研究, 2024.01-2027.12, (参与)