刘晓芳

2023年03月01日 16:36  点击:[]

基本信息

姓名:刘晓芳

性别:女

所属部门:机器人与信息自动化研究所

行政职务

职称:副教授

学历:博士

所学专业:计算机科学与技术

办公电话

电子邮件:liuxiaofang@nankai.edu.cn

研究方向群体智能、机器学习、深度学习

个人简介

◆ 2024.01    -     今,威尼斯7798cc,威尼斯7798cc,副教授

◆ 2020.09-2023.12,威尼斯7798cc,威尼斯7798cc,讲师

◆ 2015.08-2020.06,中山大学,计算机科学与技术,博士

◆ 2011.09-2015.06,中山大学,计算机科学与技术,学士

 ★ 刘晓芳,副教授,硕士生导师,主要研究领域是群体智能、机器学习、深度学习。具体研究方向包括:(1)面向复杂优化的群体智能、机器学习、大模型研究及其应用(计算资源调度、多机器人协同、交通调度等);(2)面向医学图像处理的深度学习方法研究(医学成像)。

  IEEE高级会员,目前已收录/发表学术论文40余篇,一作/通讯SCI期刊论文18篇,包括16篇中科院一区、13篇IEEE Transactions论文;ESI高被引论文3篇,成果被同行引用2000余次(近五年超过1660次),一作单篇最高引400余次。2020年入选威尼斯7798cc“学科振兴计划”,曾获得谷歌Anita Borg奖学金。 指导本科生获得2023年威尼斯7798cc优秀本科毕业设计, 指导本科生获得国家公派留学博士资助(本科期间指导发表2篇国际会议论文),指导本科生国创/百创项目。

实验室成员

钱*,2022级,硕士生,本科毕业于东北大学(已转博)

高*,2022级,硕士生,本科毕业于威尼斯7798cc

戴扬*,2023级,硕士生,本科毕业于威尼斯7798cc

陈永*,2024级,硕士生,本科毕业于威尼斯7798cc

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,与我一起学习,朝同一个梦想前进。真心想做研究的学生,我会手把手教。

研项目、成果、获奖、专利

主持国家自然科学基金面上项目(2025-2028)

主持国家自然科学青年基金(2022-2024)

◆ 主持天津市自然科学青年基金(2021-2023)

撰写论文、专著、教材等

代表性期刊论文

[1] Yang-Tao Dai (硕士生), Xiao-Fang Liu* (刘晓芳,通讯作者),  Yongchun Fang, Zhi-Hui Zhan, Jun Zhang,  “Multi-source knowledge fusion based on graph attention networks for many-task optimization,” IEEE Transactions on Evolutionary Computation, 2024, DOI: 10.1109/TEVC.2024.3465542. (中科院SCI一区Top期刊, IF=14.3)

[2] Tong Qian (硕士生), Xiao-Fang Liu* (刘晓芳,通讯作者),  Yongchun Fang, “A cooperative ant colony system for multiobjective multirobot task allocation with precedence constraints,” IEEE Transactions on Evolutionary Computation, 2024, DOI: 10.1109/TEVC.2024.3364493. (中科院SCI一区Top期刊, IF=14.3)

[3] Xiao-Fang Liu (刘晓芳), Zhi-Hui Zhan, Jun Zhang, Transfer-Based Particle Swarm Optimization for Large-Scale Dynamic Optimization With Changing Variable Interactions,IEEE Transactions on Evolutionary Computation, 2023, accepted, DOI:10.1109/TEVC.2023.3326327. (中科院SCI一区Top期刊, IF=14.3)

[4] Xiao-Fang Liu (刘晓芳), Jun Zhang, Jun Wang Cooperative Differential Evolution With an Attention-Based Prediction Strategy for Dynamic Multiobjective Optimization,IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, accpeted, DOI: 10.1109/TSMC.2023.3298804. (中科院SCI一区Top期刊, IF=11.471)

[5] Xiao-Fang Liu (刘晓芳), Yongchun Fang, Zhi-Hui Zhan,  Yun-Liang Jiang, Jun Zhang, “A cooperative evolutionary computation algorithm for dynamic multiobjective multi-auv path planning,” IEEE Transactions on Industrial Informatics, 2023, accepted, DOI: 10.1109/TII.2023.3268760.(ESI高被引论文,中科院SCI一区Top期刊, IF=11.648)

[6] Xiao-Fang Liu (刘晓芳), Xin-Xin Xu, Zhi-Hui Zhan, Yongchun Fang, Jun Zhang, “Interaction-based prediction for dynamic multiobjective optimization,” IEEE Transactions on Evolutionary Computation, 2023, accepted, DOI: 10.1109/TEVC.2023.3234113. (中科院SCI一区Top期刊, IF=14.3)

[7] Xiao-Fang Liu (刘晓芳), Yongchun Fang, Zhi-Hui Zhan, Jun Zhang, “Strength learning particle swarm optimization for multiobjective multirobot task scheduling,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, accpeted, DOI: 10.1109/TSMC.2023.3239953. (中科院SCI一区Top期刊, IF=11.471)

[8] Xiao-Fang Liu (刘晓芳), Jun Zhang, and Jun Wang, “Cooperative particle swarm optimization with a bilevel resource allocation mechanism for large-scale dynamic optimization,” IEEE Transactions on Cybernetics, vol. 53, no. 2, pp. 1000-1011, 2023. (中科院SCI一区Top期刊, IF=19.118)

[9] Xiao-Fang Liu (刘晓芳), 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, vol. 33, no. 1, pp. 6286-6296, 2022.(中科院SCI一区Top期刊,IF=14.255)

[10] Xiao-Fang Liu (刘晓芳), 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=14.255)

[11] Xiao-Fang Liu(刘晓芳), 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=14.3)

[12] Xiao Fang Liu(刘晓芳), 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=14.3)

[13] Xiao-Fang Liu(刘晓芳), 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=11.471)

讲授课程

◆ 机器视觉技术(本科生)

◆ 离散数学(本科生)

社会兼职

◆ IEEE高级会员、自动化学会会员

◆ 中国图学学会图学大数据专业委员会委员、中国人工智能学会青年工作委员会委员






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