|
周爱民职称： 研究员 直属机构： 计算机科学与技术学院 学科： |
|
|
|
10 访问 |
相关教师 |
个人资料
教育经历2004.10-2009.06：英国Essex大学计算机与电子工程学院，获博士学位 2003.09-2004.09：武汉大学计算机学院，博士在读 2001.09-2003.06：武汉大学计算机学院，获硕士学位（提前毕业） 1997.09-2001.06：武汉大学计算机学院，获学士学位 工作经历2016.12-：华东师范大学，研究员 2012.12-2016.12：华东师范大学，副教授 2009.06-2012.12：华东师范大学，讲师 个人简介社会兼职IEEE高级会员 中国计算机学会(CCF)会员 Swarm and Evolutionary Computation副编 Complex & Intelligent Systems编委 Chinese Journal of Electronics编委 IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Computational Intelligence Magazine, Pattern Recognition, Information Sciences, 软件学报，计算机学报，CEC, GECCO, EMO, IJCAI, AAAI, NeurIPS等期刊和会议审稿人 国家自然科学基金通讯评审专家（2011-2021） 研究方向演化搜索与优化(Evolutionary Search and Optimization) 智能教育(AI for Education) 工业应用(Industry Applications) 开授课程计算机导论，本科必修，2022 智能教育，本科师范生选修课，2022 人工智能前沿专题，博士生必修，2021 AIoT智能系统，研究生选修，2021 人工智能前沿，研究生必修，2018-2020 计算智能，研究生必修，2012-2016 最优化方法，研究生选修，2016-2017 Windows程序设计，本科选修，2012 编程实践，本科必修，2010-2012 科研项目[7] 数据驱动与知识引导的可解释性机器学习模型构建理论与方法，上海市科委人工智能专项，2019年-2022年，项目号：19511120600，主持人。 [6] 面向数据的快速磁共振成像 ，自然科学基金重点项目，2018年-2022年，项目号：61731009，主要参与者。 [5] 模型辅助演化多目标优化及应用，自然科学基金面上项目，2017年-2020年，项目号：61673180，主持人。 [4] 基于学习技术的多目标进化算法重组算子研究，自然科学基金面上项目，2013年-2016年，项目号：61273313，主持人。 [3] 便携式拉曼光谱仪研制，科技部重大仪器专项课题，2012年-2017年，项目号：2012YQ180132-01，子课题主持人。 [2] 多源异质数据的信息提取与快速变化检测，科技部973计划项目课题，2011年-2015年，项目号：2011CB707104，主要参与者。 [1] 求解多目标旅行商问题的分布估计算法研究，自然科学基金青年项目，2011年，项目号：44102330，主持人。 学术成果Google Citation:http://scholar.google.com/citations?user=E4GQv5cAAAAJ&hl=en DBLP:https://dblp.uni-trier.de/pers/hd/z/Zhou:Aimin 主要论文： [1].H. Zhang, A. Zhou, H. Qian, and H. Zhang, PS-Tree: A piecewise symbolic regression tree. Swarm and Evolutionary Computation, 2022. (accepted) [2].H. Hao, A. Zhou, H. Qian, and H. Zhang, Expensive multiobjective optimization by relation learning and prediction, IEEE Transactions on Evolutionary Computation, 2022. (accepted) [3].H. Zhang, A. Zhou, and H. Zhang, An evolutionary forest for regression, IEEE Transactions on Evolutionary Computation, 2022. (accepted) [4].Y. Qian, X. Li, J. Wu, A. Zhou, Z. Xu, and Q. Zhang, Picture-word order compound protein interaction: Predicting compound-protein interaction using structural images of compounds, Journal of Computational Chemistry, 43(4):255-264,2022. [5].Y. Chen, A. Zhou, and S. Das, Utilizing dependence among variables in evolutionary algorithms for mixed-integer programming: A case study on multi-objective constrained portfolio optimization, Swarm and Evolutionary Computation, 66(2021) 100928, 2021. [6].F. Wang, H. Zhang, and A. Zhou, A particle swarm optimization algorithm for mixed-variable optimization problems, Swarm and Evolutionary Computation, 60(2021)100808, 2021. [7].C. Liu, T. Bian, and A. Zhou, Multiobjective multiple features fusion: A case study in image segmentation, Swarm and Evolutionary Computation, 60(2021)100792, 2021. [8].M. Yang, A. Zhou, X. Yao, and C. Li, An efficient recursive differential grouping for large-scale continuous problems, IEEE Transactions on Evolutionary Computation, 25(1):159-171, 2021. [9].H. Hao, J. Zhang, X. Lu, and A. Zhou, Binary relation learning and classifying for preselection in evolutionary algorithms, IEEE Transactions on Evolutionary Computation, 24(6):1125-1139, 2020. [10].F. Wang, Y. Li, A. Zhou, and K. Tang, An estimation of distribution algorithm for mixed-variable Newsvendor problems, IEEE Transactions on Evolutionary Computation, 24(3):479-493, 2020. [11].张晋媛, 周爱民, 张桂戌, 演化算法中一种基于单分类的预选择策略, 计算机学报, 43(2):233-249, 2020. [12].M. Yang, A. Zhou, C. Li, J. Guan, and X. Yan, CCFR2: A more efficient cooperative co-evolutionary framework for large-scale global optimization, Information Sciences, 512:64-79, 2020. [13].A. Zhou, Y. Wang, and J. Zhang, Objective extraction via Fuzzy clustering in evolutionary many-objective optimization, Information Sciences, 509:343-355, 2020. [14].陈晓纪, 石川, 周爱民, 吴斌, 一种基于混合个体选择机制的多目标进化算法, 软件学报, 30(12):3651-3664, 2019. [15].A. Zhou, J. Zhang, J. Sun, and G. Zhang, Fuzzy-classification assisted solution preselection in evolutionary optimization, in AAAI, pp. 2403-2410, 2019. [16].J. Sun, H. Zhang, A. Zhou, Q. Zhang, K. Zhang, Z. Tu, and K. Ye, Learning from a stream of nonstationary and dependent data in multiobjective evolutionary optimization, IEEE Transactions on Evolutionary Computation, 23(4):541-555, 2019. [17].W. Hong, K. Tang, A. Zhou, H. Ishibuchi, and X. Yao, A scalable indicator-based evolutionary algorithm for large-scale multi-objective optimization, IEEE Transactions on Evolutionary Computation, 23(3):525-537, 2019. [18].J. Sun, H. Zhang, A. Zhou, Q. Zhang, and K. Zhang, A new learning-based adaptive multi-objective evolutionary algorithm, Swarm and Evolutionary Computation, 44:304-319, 2019. [19].J. Zhang, A. Zhou, K. Tang, and G. Zhang, Preselection via classification: A case study on evolutionary multiobjective optimization, Information Sciences, 465:388-403, 2018. [20].H. Fang, A. Zhou, and H. Zhang, Information fusion in offspring generation: A case study in DE and EDA, Swarm and Evolutionary Computation, 42:99-108, 2018. [21].J. Sun, A. Zhou, S. Keates, and S. Liao, Simultaneous Bayesian clustering and feature selection through student’s t mixtures model, IEEE Transactions on Neural Networks and Learning Systems, 29(4):1187-1199, 2018. [22].H. Zhang, A. Zhou, S. Song, Q. Zhang, X. Gao, and J. Zhang, A self-organizing multiobjective evolutionary algorithm, IEEE Transactions on Evolutionary Computation, 20(5):792-806, 2016. [23].L. Wang, Q. Zhang, A. Zhou, M. Gong, and L. Jiao, Constrained subproblems in decomposition based multiobjective evolutionary algorithm, IEEE Transactions on Evolutionary Computation, 20(3):475-480, 2016. [24].A. Zhou, and Q. Zhang, Are all the subproblems equally important? Resource allocation in decomposition based multiobjective evolutionary algorithms, IEEE Transactions on Evolutionary Computation, 20(1):52-64, 2016. [25].Z. Wang, Q. Zhang, A. Zhou, M. Gong, and L. Jiao, Adaptive replacement strategies for MOEA/D, IEEE Transactions on Cybernetics, 46 (2):474-486, 2016. [26].A. Zhou, J. Sun, and Q. Zhang, An estimation of distribution algorithm with cheap and expensive local search, IEEE Transactions on Evolutionary Computation, 19 (6): 807-822, 2015. [27].W. Gong, A. Zhou, and Z. Cai, A multi-operator search strategy based on cheap surrogate models for evolutionary optimization, IEEE Transactions on Evolutionary Computation, 19 (5): 746-758, 2015. [28].A. Zhou, Y. Jin, and Q. Zhang, A population prediction strategy for evolutionary dynamic multiobjective optimization, IEEE Transactions on Cybernetics, 44(1):40-53,2014. [29].周爱民, 张青富, 张桂戌, 一种基于混合高斯模型的多目标进化算法, 软件学报, 5:913-928, 2014. [30].A. Zhou, F. Gao, and G. Zhang, A decomposition based estimation of distribution algorithm for multiobjective traveling salesman problems, Computers and Mathematics with Applications, 66:1857–1868, 2013. [31].A. Zhou, B. Qu, H. Li, S. Zhao, P. Suganthan, and Q. Zhang, Multiobjective evolutionary algorithms: A survey of the state of the art, Swarm and Evolutionary Computation, 1(1): 32–49, 2011. [32].A. Zhou, Q. Zhang and Y. Jin, Approximating the set of Pareto optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm,IEEE Transactions on Evolutionary Computation, 13(5):1167-1189, 2009. [33].Q. Zhang, A. Zhou, and Y. Jin, RM-MEDA: A regularity model based multiobjective estimation of distribution algorithm, IEEE Transactions on Evolutionary Computation, 12(1):41-63, 2008. 学位论文： [1].博士论文: Estimation of distribution algorithms for continuous multiobjective optimization, University of Essex, 2009年, 导师: Qingfu Zhang教授, Edward Tsang教授, Yaochu Jin教授(Honda Research Institute Europe), Bernhard Sendhoff博士(Honda Research Institute Europe). [2].硕士论文: 演化建模及其应用, 武汉大学, 2003年, 导师: 康立山教授. 荣誉及奖励 |
