周李达，硕士毕业于早稻田大学情报生产系统研究科，曾任中国银行湖北省银行信息科技部助理技术经理。现任计算机与自动化学院软件工程系专职教师岗位。研究方向：机器学习，着重于聚类密度算法。主要担任课程： C语言课程设计、移动项目实训、JAVA项目实训。主要发表论文：[1]Yewang Chen, Lida Zhou, Yi Tang, Nizar Bouguila, Huazhen Wang. Fast Neighbor Search By Using Revised K-D Tree. Information Sciences. 2019, vol(472): 145-162 ( SCI, IF 4.732,中科院 小类 1 区，top 期刊，检索号：S0020025518307126-)[2] Yewang Chen, Lida Zhou, Nizar Bougulia etl. Semi-Convex Hull Tree: Fast Neighbor Query Algorithm on GPUs. //2018 IEEE International Conference on Data Mining (ICDM). IEEE, 2018: 911-916 (数据挖掘顶级学术会议，EI 收录，检索号：WOS:000464691700096)[3]Yewang Chen, Lida Zhou, Lianlian Sheng et al. KNN-BLOCK DBSCAN: Fast Clustering For Large Scale Data. IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 6, pp. 3939-3953, June 2021 ( SCI, IF 13.45, 中科院1 区，top期刊，高被引)[4]Yewang Chen, Lida Zhou, Nizar Bouguila et al . BLOCK-DBSCAN: Fast Clustering For Large Scale Data. Pattern recognition. Volume 109, 2021, 107624,10.1016/j.patcog.2020.107624. (SCI, IF 7.74,中科院2区,高被引)
