刘晓芳 - 南开大学 - 人工智能学院

个人简介

个人简介 ◆ 讲师, 2020.09-今，南开大学 ◆ 博士, 2015.08-2020.06，中山大学，计算机科学与技术 ◆ 学士, 2011.09-2015.06，中山大学，计算机科学与技术刘晓芳，现为南开大学人工智能学院讲师，主要研究领域是群体智能、进化计算、机器学习及其应用。具体研究方向包括：（1）面向动态、多目标、大规模等复杂优化问题的进化算法、群体智能、机器学习算法研究及其应用（资源调度、多机器人协同等）；（2）深度学习在磁共振全周期成像中的应用研究，包括：图像采集、图像重建、图像处理和疾病诊断。目前已发表国际期刊SCI论文以及EI会议论文近20篇，包括IEEE Transactions论文6篇（一作5篇），中科院SCI一区Top期刊论文6篇；ESI高被引论文2篇，成果近5年被同行引用900余次。2020年入选南开大学人工智能学院“学科振兴计划”，获得谷歌Anita Borg奖学金。正在招收硕士研究生，非常欢迎校内外保研、考研、对相关研究感兴趣的同学联系我（liuxiaofang@nankai.edu.cn）；也欢迎想提前进入实验室参与科研训练的本科生咨询，一起朝同一个梦想前进。真心想做研究的学生，我会手把手教。讲授课程 ◆ 机器视觉技术

研究领域

群体智能、进化计算、机器学习及其应用，如云资源调度、多机器人系统、医学影像处理等

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

[1] Xiao-Fang Liu (刘晓芳), Zhi-Hui Zhan, et al., “Resource-aware distributed differential evolution for training expensive neural-network-based controller in power electronic circuit,” IEEE Transactions on Neural Networks and Learning Systems, accepted, 2021. (中科院SCI一区Top期刊，IF=8.793) [2] Xiao-Fang Liu (刘晓芳), Zhi-Hui Zhan, et al., “Neural network-based information transfer for dynamic optimization,” IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 5, pp. 1557-1570, 2020. (中科院SCI一区Top期刊，IF=8.793) [3] Xiao-Fang Liu(刘晓芳), Zhi-Hui Zhan, et al., “Coevolutionary particle swarm optimization with bottleneck objective learning strategy for many-objective optimization,” IEEE Transactions on Evolutionary Computation, vol. 23, no. 4, pp. 587-602, 2019. (中科院SCI一区Top期刊，IF=11.169) [4] Xiao Fang Liu(刘晓芳), Zhi-Hui Zhan, et al., “An energy efficient ant colony system for virtual machine placement in cloud computing,” IEEE Transactions on Evolutionary Computation, vol. 22, no. 1, pp. 113-128, 2018. (ESI高被引论文,中科院SCI一区Top期刊，IF=11.169) [5] Xiao-Fang Liu(刘晓芳), Zhi-Hui Zhan, et al., “Historical and heuristic-based adaptive differential evolution,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 12, pp. 2623-2635, 2019. (中科院SCI一区Top期刊，IF=9.309) [6] Zhi-Hui Zhan, Xiao-Fang Liu(刘晓芳), et al., “Cloudde: A heterogeneous differential evolution algorithm and its distributed cloud version,” IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 3, pp. 704-716, 2017. (CCF A类期刊) [7] Zhi-Hui Zhan, Xiao-Fang Liu(刘晓芳), et al., “Cloud computing resource scheduling and a survey of its evolutionary approaches,” ACM Computing Surveys, vol. 47, no. 4, 63, pp. 1-33, 2015. (ESI高被引论文，中科院SCI一区Top期刊) [8] Xiao-Fang Liu(刘晓芳), Yuren Zhou, et al., “Dual-archive-based particle swarm optimization for dynamic optimization,” Applied Soft Computing, vol. 85, 105876, 2019. (IF=5.472) [9] Xiao-Fang Liu(刘晓芳), Yuren Zhou, et al., “Cooperative particle swarm optimization with reference-point-based prediction strategy for dynamic multiobjective optimization,” Applied Soft Computing, vol. 87, 105988, 2020. (IF=5.472) [10] Xiao-Fang Liu(刘晓芳), Zhi-Hui Zhan, et al., “Neural network for change direction prediction in dynamic optimization,” IEEE Access, vol. 6, pp. 72649-72662, 2018. (IF=3.745) [11] Xiao-Fang Liu(刘晓芳), Zhi-Hui Zhan, et al., “An energy aware unified ant colony system for dynamic virtual machine placement in cloud computing,” Energies, vol. 10, no. 5, 609, pp. 1-15, 2017. [12] Xue Yu, Yuren Zhou, and Xiao-Fang Liu(刘晓芳), “A novel hybrid genetic algorithm for the location routing problem with tight capacity constraints,” Applied Soft Computing, vol. 85, 105760, 2019. [13] Xue Yu, Yuren Zhou, and Xiao-Fang Liu(刘晓芳), “The two-echelon multi-objective location routing problem inspired by realistic waste collection applications: The composable model and a metaheuristic algorithm,” Applied Soft Computing, vol. 94, 106477, 2020.

学术兼职

◆ IEEE Transactions on Evolutionary Computation、IEEE Transactions on Neural Networks and Learning System、IEEE Transactions on Cybernetics等多个期刊会议审稿人 ◆ IEEE会员