程东东，毕业于重庆大学计算机学院，博士，副教授,巴渝学者-青年学者，重庆邮电大学兼职硕导。
研究方向：数据挖掘、机器学习、模式识别
主要承担的课程：物联网数据处理技术、Python程序设计、大数据导论、Hadoop大数据技术
研究成果：本人主要从事聚类算法和聚类结果评估方法的研究，提出了局部核心点的概念，在聚类分析中用于降低数据规模，同时在此基础上进行了新的聚类算法的研究，有效解决了复杂流形数据的聚类具有高时间复杂度的问题。
相关论文：
[1] Cheng D, Liu S, Xia S, Wang G. Granular-ball computing-based manifold clustering algorithms for ultra-scalable data[J]. Expert Systems With Applications, 2024, 247, 123313.
[2] Cheng D, Luo J, Huang J, Zhang S. Searching natural neighbors in an accelerated way[J]. Engineering Applications of Artificial Intelligence, 2023, 126, 107172.
[3] Cheng D, Li Y, Xia S, Wang G, Huang J, Zhang S. A fast granular-ball-based density peaks clustering algorithm for large scale data[J], IEEE Transactions on Neural Networks and Learning Systems, 2023. doi: 10.1109/TNNLS.2023.3300916.
[4] Cheng D, Huang J, Zhang S, Xia S, Wang G, Xie J. K-means clustering with natural density peaks for discovering arbitrary-shaped clusters [J]. IEEE Transactions on Neural Networks and Learning Systems, 2023. DOI: 10.1109/TNNLS.2023.3248064. (SCI 1区)
[5] Cheng D, Huang J, Zhang S, Zhang X, Luo X. A novel approximate spectral clustering algorithm with dense cores and density peaks [J], IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 52(4):2348-2360. DOI: 10.1109/TSMC.2021.3049490. (SCI 1区)
[6] Cheng D, Zhu Q, Huang J, Wu Q, Yang L, Clustering with local density peaks-based minimum spanning tree[J], IEEE Transactions on Knowledge and Data Engineering, 2021, 33(2), 374-387. DOI: 10.1109/TKDE.2019.2930056. (SCI 2区，CCF-A)
[7] Cheng D, Zhu Q, Huang J, Wu Q, Yang L, A novel cluster validity index based on local cores [J], IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(4): 985-999. DOI: 10.1109/TNNLS.2018.2853710. (SCI 1区)
[8] Cheng D, Zhu Q, Huang J, Yang L, Wu Q, Natural neighbor-based clustering algorithm with local representatives [J], Knowledge-Based Systems, 2017, 123:238-253.（SCI 1区）
[9] Cheng D, Zhang S, Huang J. Dense members of local cores-based density peaks clustering algorithm [J], Knowledge-Based Systems, 2020, 193: 105454. (SCI 1区)
[10] Cheng D, Zhu Q, Huang J, Wu Q. A local cores-based hierarchical clustering algorithm for data sets with complex structures [J], Neural Computing & Applications, 2019, 31(11), 8051-8068. DOI: 10.1007/s00521-018-3641-8. (SCI 2区)
[11] Cheng D, Zhu Q, Huang J, Wu Q, Yang L, A hierarchical clustering algorithm based on Noise Removal [J], International Journal of Machine Learning and Cybernetics, 2019, 10(7), 1591-1602. DOI: 10.1007/s13042-018-0836-3. (SCI 3区)
[12] Cheng D, Huang J, Zhang S, Liu H. Improved Density peaks clustering based on shared-neighbors of local cores of manifold data sets [J], IEEE ACCESS, 2019, 7:151339-151349.
[13] Cheng D, Huang J, Zhang S, et al. A robust method based on locality sensitive hashing for K-nearest neighbors searching. Wireless Networks, 2022, online, DOI: 10.1007/s11276-022-02927-9.
[14] Wang G, Cheng D, Xia D, Jiang H. Swarm Intelligence Research: From Bio-inspired Single-population Swarm Intelligence to Human-machine Hybrid Swarm Intelligence[J]. Machine Intelligence Research, 2023, 20(1): 121-144.
[15] Cheng D, Zhu Q, Huang J, et al. Natural neighbor-based clustering algorithm with density peeks[C]// International Joint Conference on Neural Networks (IJCNN), Vancouver, 2016: 92-98. （CCF-C）
[16] Cheng D, Zhu Q, Wu Q. A local cores-based hierarchical clustering algorithm for data sets with complex structures[C]// The 42nd IEEE Computer Society Signature Conference on Computers, Software and Applications (COMPSAC), Tokyo, 2018: 410-419. （CCF- C）
专著：
[1] 程东东，黄金龙，朱庆生. 基于自然邻居的聚类分析和离群检测算法研究[M]. 上海交通大学出版社，2019.11.
相关项目：
(1) 国家自然科学基金青年科学基金项目：62006029，基于局部核心点的高光谱图像聚类研究，2021. 01-2023. 12, 24万元，已结题，主持
(2) 重庆市博士后创新人才支持计划：CQBX2021024，基于局部核心点的多粒度模型构建研究，2022.1-2024.12，60万元，在研，主持
(3) 重庆市自然科学基金面上项目：cstc2019jcyj-msxmX0683, 基于局部核心点聚类分析的3D点云骨架提取研究，2019.07-2022.06, 10万元，已结题，主持
(4) 重庆市自然科学基金面上项目：CSTB2022NSCQ-MSX0258，基于复杂流形聚类的高光谱图像波段选择方法研究，2022.8-2025.7, 10万元，在研，主持
(5) 重庆市教委科技项目青年项目：KJQN202001434，基于数据挖掘的树木骨架提取研究，2020.10-2023.10，已结题，主持
(6) 重庆市教委科技项目重点项目：KJZD-K202301402，基于多粒度表示的高光谱聚类研究，2023.10-2026.10，在研，主持
获奖：以第一完成人获2022年度重庆市自然科学奖三等奖，首届川渝科技学术大会优秀论文三等奖，涪陵区第十三届自然科学优秀学术论文二等奖。
联系方式：cdd@yznu.edu.cn
