主要从事构建基于相关、非同以及无界抽样的核机器学习理论和方法，建立分布式学习和贪婪学习等算法的最优收敛阶。近五年主持国家自然科学基金青年基金、山东建筑大学博士基金各1项，参与国家自然科学基金2项，参与山东省青创团队2项。第一作者或通讯作者在国内外重要期刊上发表论文20余篇，申请专利2项，其中第一作者论文被SCI收录11篇。主要承担《概率论与数理统计》、《统计软件SPSS》、《统计实验SPSS》等课程的教学工作。2019年获评理学院第十五届青年教师讲课比赛一等奖，山东建筑大学青年教师教学比赛二等奖，2013年获评首届山东省高等学校教师微课教学比赛三等奖。 代表性科研成果： 1. Qin Guo (郭芹)*, Xianghua Liu, Peixin Ye. The learning performance of the weak rescaled pure greedy algorithms. Journal of Inequalities and Applications, 30:1-14, 2024. (第一作者/通讯作者， SCI, IF:2.491, JCR分区Q1) 2. Qin Guo (郭芹)*, Binlei Cai (蔡斌雷). Learning capability of the rescaled pure greedy algorithm with non iid sampling, Electronic Research Archive, 2023, 31(3): 1387-1404 (第一作者/通讯作者，SCI, IF:0.8, JCR分区Q3) 3. Binlei Cai; Qin Guo; Xiaodong Dong. AutoInfer: Self-Driving Management for Resource-Efficient, SLO-Aware Machine=Learning Inference in GPU Clusters, IEEE Internet of Things Journal, 2023, 10(7): 6271-6285. SCIE. 4.Binlei Cai; Bin Wang; Meihong Yang; Qin Guo. AutoMan: Resource-efficient provisioning with tail latency guarantees for microservices, Future Generation Computer Systems, 2023, 143: 143-75. 5. Qin Guo. Distributed Semi-supervised Regression Learning with Coefficient Regularization, Results in Mathematics, 2022, 77(2): 1-19. (第一作者/通讯作者，SCI, IF:1.7, JCR分区Q1) 6. Binlei Cai; Qin Guo; Junfeng Yu. LraSched: Admitting More Long-Running Applications via Auto-Estimating Container Size and Affinity. The Computer Journal, 2021, 65(9): 2377-2391. 7.Qin Guo (郭芹)*, Peixin Ye (叶培新). Error analysis of the moving least-squares regression learning algorithm with β-mixing and non-identical sampling. International Journal of Computer Mathematics, 97(8): 1586-1602, 2020. (第一作者/通讯作者，SCI, IF:1.931, JCR分区Q2) 8. Qin Guo (郭芹)，Peixin Ye (叶培新) *. Error analysis of the moving least-squares method with non-identical sampling. International Journal of Computer Mathematics, 96(4): 767-781, 2019. (第一作者，SCI, IF:1.931, JCR分区Q2) 9. Qin Guo (郭芹)*, Peixin Ye (叶培新). Error analysis for lq-coefficient regularized moving least-square regression. Journal of Inequalities and Applications, 262:1-15, 2018. (第一作者/通讯作者， SCI, IF:2.491, JCR分区Q1) 10. Qin Guo (郭芹), Cheng Wang (王承) *，Peixin Ye (叶培新). Coefficient-based lq-regularized regression with indefinite kernels and unbounded sampling. Journal of Approximation Theory, 236: 1-22, 2018. (第一作者，SCI, IF:1.091, JCR分区Q2) 11. Qin Guo(郭芹) *，Peixin Ye (叶培新). Error Analysis of Least-Squares lq-Regularized Regression Learning Algorithm With the Non-Identical and Dependent Samples. IEEE Access, 2018, 6: 43824-43829. SCIE. (第一作者/通讯作者，SCI, IF: 3.557, JCR分区Q1) 12. Qin Guo(郭芹) *，Peixin Ye (叶培新) , Binlei Cai (蔡斌雷). Convergence Rate for lq-Coefficient Regularized Regression With Non-i.i.d. Sampling. IEEE Access, 2018, 6, pp. 18804-18813, DOI: 10.1109/ACCESS.2018.2817215 (第一作者/通讯作者，SCI, IF: 3.557, JCR分区Q1) 13. Qin Guo(郭芹) *，Peixin Ye (叶培新). Convergence rate for the moving least-squares learning with dependent sampling. Journal of Inequalities and Applications, 2018:200, DOI: 10.1186/s13660-018-1794-8 . (第一作者/通讯作者，SCI, IF: 2.491, JCR分区Q1) 14. Qin Guo(郭芹)，Peixin Ye (叶培新) *. Coefficient-based regularized regression with dependent and unbounded sampling. International Journal of Wavelets, Multiresolution and Information Processing, 14(5): 1-14, 2016. (第一作者，SCI, IF: 1.408, JCR分区Q3) 15. Hongwei Sun(孙红卫), Qin Guo（郭芹）. Coefficient regularized regression with non-iid sampling. International Journal of Computer Mathematics, 2011, 88(15): 3113-3124, DOI: 10.1080/00207160.2011.587511. . (SCI, IF:1.931, JCR分区Q2) 16.一种基于混合粒度分布式内存网格索引的KNN查询方法, 发明专利: 2015104815947. (第三位) 主持的科研项目： 1.国家自然科学基金青年基金项目，基于相关、非同以及无界抽样的核机器学习算法的一致性研究，2021.01-2023.12，24万元，主持. 2.山东建筑大学校博士基金,一般框架下系数正则化学习算法的学习理论研究,2019.12-2022.12 20万元，主持. 获得的奖励： 2013年 山东省第一届高等学校教师微课教学比赛三等奖2019年 理学院第十五届青年教师讲课比赛一等奖 2019年 山东建筑大学青年教师教学比赛二等奖
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