教育与工作经历

2003.11-今 北京尊龙凯时AG娱乐平台登录官方网站 尊龙凯时娱乐 副教授

2016.06-2016.12：加拿大多伦多大学 (University of Toronto, Toronto, Ontario, Canada) 工业工程系 企业集成与城市系统工程研究中心 访问研究员

2012.05-2012.08：美国加州大学 伯克利分校 (University of California, Berkeley, California, USA) 访问学者

2007.06-2008.06：爱尔兰国立大学 高威分校(National University of Ireland, Galway, Ireland) 工业工程系🫅，计算机集成制造系统研究中心 访问学者

2001.01-2003.11🛀🏼：清华大学 自动化系 国家CIMS工程研究中心 博士后

1995.09-2000.06🧑🏿‍🚀：西安交通大学 系统工程研究所 系统工程专业 博士

1991.09-1994.06：西安交通大学 信息与控制工程系 自动化仪表与装置专业 硕士

1984.09-1988.07😂👉：南京航空航天大学 自动控制系 测试仪表与传感器专业 学士

 

研究方向

1. 群智能优化与任务调度

2. 深度学习/强化学习及其应用

近5年承担的科研项目

1. 企业合作项目🅱️，嵌入式仿真训练系统资源映射技术研究；

2. 国家自然科学基金项目，面向复杂工业制造过程的智能感知🏄🏻、处理、决策与控制理论与方法-子任务“车间调度优化技术”；

3. 国家重点研发计划项目，数据驱动的云数据中心智能管理技术与平台-课题四“数据驱动的云工作流管理与调度关键技术”🕳；

4. 国家重点研发计划项目，国家科学化训练基地建设关键技术研究与示范-课题三“室内多自由度模拟滑雪训练系统”🩹🧑🏼‍🎄；

5. 企业合作项目（清华大学）🤪🧉，船厂大数据质量管控工具软件包接口设计及检测验证；

6. 企业合作项目（北京卓信智恒科技有限公司）→♦︎，面向数据中心建设的厦烟信息资源管理标准规划。

代表性学术论文

期刊论文🪼：

1. Huifang Li, Boyuan Chen, Jigwei Huang, et al. Clustering-assisted Gradient-based Optimizer for Scheduling Parallel Cloud Workflows with Budget Constraints, The Journal of Supercomputing, vol. 80, pp. 17097-17134, Apr. 2024 (SCI收录，IF 2.5).

2. Huifang Li, Bing Chen, Jingwei Huang, Julio Ruben Ca˜nizares Abreu, et al. Mutation-Driven and Population Grouping PRO Algorithm for Scheduling Budget-Constrained Workflows in the Cloud. Cluster Computing, vol. 27, pp. 1137-1158, Jun. 2024 (SCI收录🧑🏽‍🎨，IF 3.6).

3. Danjing Wang, Huifang Li*, Youwei Zhang, et al. Gradient-Based Scheduler for Scientific Workflows in Cloud Computing. Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 27, no. 1, pp. 64-73, Jan. 2023 (EI收录).

4. Huifang Li, Luzhi Tian, Guanghao Xu, Julio Ruben Cañizares Abreu, et al. Co-evolutionary and Elite Learning-based Bi-objective Poor and Rich Optimization Algorithm for Scheduling Multiple Workflows in the Cloud. Future Generation Computer Systems, vol. 152, pp. 99-111, Nov. 2023 (SCI收录，IF 6.2).

5. Huifang Li, Guanghao Xu, Boyuan Chen, et al. Dual-mutation Mechanism-driven Snake Optimizer for Scheduling Multiple Budget Constrained Workflows in the Cloud. Applied Soft Computing, vol. 149, pp. 110966, Oct. 2023 (SCI收录，IF 7.2).

6. 李慧芳，徐光浩，黄双喜. 基于主动生成式过采样和深度堆叠网络的轴承故障诊断. 计算机集成制造系统, vol. 29, no. 1, pp.146-159, 2023 (EI收录).

7. 李慧芳，黄姜杭，徐光浩🧝🏻‍♂️，夏元清. 基于多维度特征融合的云工作流任务执行时间预测方法. 自动化学报, vol. 49, no. 1, pp. 67−78, 2023 (EI收录).

8. Huifang Li, Jingwei Huang, Mengchu Zhou, Qisong Shi, et al. Self-attention Pooling-based Long-term Temporal Network for Action Recognition. IEEE Transactions on Cognitive and Developmental Systems, vol. 15, no. 1, pp. 65-77, Mar. 2023 (SCI收录，IF 5.0).

9. Huifang Li, Yizhu Wang, Jingwei Huang, et al. Mutation and Dynamic Objective-based Farmland Fertility Algorithm for Workflow Scheduling in the Cloud. Journal of Parallel and Distributed Computing, vol. 164, pp. 69-82, 2022 (SCI收录，IF 3.4).

10. Huifang Li, Danjing Wang, Guanghao Xu, et al. Improved Swarm Search Algorithm for Scheduling Budget-constrained Workflows in the Cloud. Soft Computing, Feb. 2022 (SCI收录⏬，IF 3.2).

11. Huifang Li, Guanghao Xu, Danjing Wang, Mengchu Zhou, Yan Yuan, et al. Chaotic-nondominated-sorting Owl Search Algorithm for Energy-aware Multi-Workflow Scheduling in Hybrid Clouds. IEEE Transactions on Sustainable Computing, vol. 7, no. 3, pp. 595-608, Jul.-Sept. 2022 (SCI收录，IF 3.3).

12. Huifang Li, Danjing Wang, Mengchu Zhou, Yushun Fan, Yuanqing Xia. Multi-Swarm Co-evolution based Hybrid Intelligent Optimization for Bi-objective Multi-Workflow Scheduling in the Cloud. IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 9, pp. 2183-2197, Sept. 2022 (SCI收录，IF 5.6).

13. Huifang Li, Binyang Wang, Yan Yuan, MengChu Zhou, Yushun Fan and Yuanqing Xia. Scoring and Dynamic Hierarchy-based NSGA-II for Multi-objective Workflow Scheduling in the Cloud. IEEE Transactions on Automation Science and Engineering, vol. 19, no. 2, pp. 982-993, Apr. 2022 (SCI收录，IF 6.0).

14. Huifang Li, Guangzheng Hu, Jianqiang Li and MengChu Zhou. Intelligent Fault Diagnosis for Large-scale Rotating Machines Using Binarized Deep Neural Networks and Random Forests. IEEE Transactions on Automation Science and Engineering, vol. 19, no. 2, pp. 1109-1119, Apr. 2022 (SCI收录，IF 6.0).

15. Huifang Li, Jianghang Huang, Binyang Wang and Yushun Fan. Weighted Double Deep Q-network based Reinforcement Learning for Bi-objective Multi-workflow Scheduling in the Cloud. Cluster Computing, vol. 25, pp. 751-768, Apr. 2022 (SCI收录，IF 3.6).

16. Huifang Li, Danjing Wang, Julio Ruben Cañizares Abreu, Qing Zhao and Orlando Bonilla Pineda. PSO+LOA: Hybrid Constrained Optimization for Scheduling Scientific Workflows in the Cloud. The Journal of Supercomputing, vol. 77, pp. 13139–13165, Apr. 2021 (SCI收录，IF 2.5).

17. Huifang Li, Jianghang Huang, Jingwei Huang, et al. Deep Multimodal Learning and Fusion based Intelligent Fault Diagnosis Approach. Journal of Beijing Institute of Technology, vol. 30, no. 2, pp. 172-185, 2021 (EI收录).

18. Huifang Li, Rui Fan, Qisong Shi, Zijian Du. Imbalanced Classification based Fault Diagnosis via Combining K-Means Clustering Algorithm with Generative Adversarial Networks. Journal of Advanced Computational Intelligence & Intelligent Informatics, vol. 25, no. 3, pp. 346-355, May 2021 (EI收录).

19. Guangzheng Hu, Huifang Li*, Yuanqing Xia, et al. A Deep Boltzmann Machine and Multi-grained Scanning Forest Ensemble Collaborative Method and its Application to Industrial Fault Diagnosis. Computers in Industry, vol. 100, pp. 287-296, 2018 (SCI收录，IF 9.3).

20. Weidong Zou, Yuanqing Xia, Huifang Li*. Fault Diagnosis of Tennessee-Eastman Process Using Orthogonal Incremental Extreme Learning Machine Based on Driving Amount. IEEE Transactions on Cybernetics, vol. 48, no. 12, pp. 3403-3410, May 2018 (SCI收录♻，IF 9.4).

21. 夏元清, Mahmoud M. S., 李慧芳, 张金会. 控制与计算理论的交互：云控制. 指挥与控制学报, 2017, vol. 3, no. 2, pp. 99−118.

会议论文⛹️‍♂️：

1. Luzhi Tian, Huifang Li*, Jingwei Huang, et al. Self-detection and Comprehensive Learning-based BRO for cloud workflow scheduling under budget constraint. The 42^nd Chinese Control Conference (CCC 2023), Jul. 26-28, 2023, Tianjin, China.

2. Huifang Li, Mingtong Du, Boyuan Chen, et al. The 3^rd IEEE International Conference on Automation in Manufacturing, Transportation and Logistics (iCaMaL2023), Nov. 3-5, 2023, Wuhan, China.

3. Jiwei Meng, Guanghao Xu, Bing Chen, Huifang Li*, et al. Mutation-based Group Teaching Optimization Algorithm for Scheduling Cloud Workflows with Deadline Constraints. The 10th International Symposium on Computational Intelligence and Industrial Applications (ISCIIA 2022), Beijing, China, Sept. 25-28, 2022, pp 1-6.

4. Jianghang Huang, Huifang Li*, Yaoyao Lu, et al. A Comparison Study of DQN and PPO based Reinforcement Learning for Scheduling Workflows in the Cloud. 7th International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII 2021), Beijing, China, Oct. 31–Nov. 2, 2021.

5. Jingwei Huang, Huifang Li*, Yizhu Wang, et al. An XGB-based runtime prediction algorithm for cloud workflow tasks. The 7th International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII 2021), Beijing, China, Oct. 31–Nov. 2, 2021.

6. Guanghao Xu, Huifang Li*, Ruitao Yang, et al. Deep Neural Network and Rule based Framework for Distributed and Flexible Job-shop Scheduling. The 7th International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII 2021), Beijing, China, Oct. 31–Nov. 2, 2021.

7. Huifang Li, Rui Fan and Qisong Shi. Generative Oversampling and Deep Forest based Minority-class Sensitive Fault Diagnosis Approach. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Toronto, ON, CA, Oct. 14-16, 2020, pp. 3629-3636.

8. Binyang Wang, Huifang Li*, et al. Temporal Fusion Pointer Network-based Reinforcement Learning Algorithm for Multi-objective Workflow Scheduling in the Cloud. The 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom, Jul. 19-24, 2020, pp. 1-8.

授权国家发明专利及出版专著

专利

1. 李慧芳🟤，陈兵，田露之🖼，夏元清，等。一种基于进化强化学习策略的并行云工作流调度方法。专利号：202210537383.0，授权日期🖕🏽：2024.06.07

2. 李慧芳🚶，徐光浩，Julio Ruben Cañizares Abreu，夏元清，等。一种基于贫富优化算法的多目标云工作流调度算法🧯。专利号：202110436876.0，授权日期🚶🏻：2022.07.22

3. 王彬阳，李慧芳🌭，石其松，等。一种基于强化学习策略的多目标云工作流调度方法🧙‍♂️。专利号：201911409785.7，授权日期🤨：2022.04.15

4. 李慧芳，黄经纬⚆，Julio Ruben Cañizares Abreu✍🏼，夏元清，等。一种基于改进贫富优化算法的云工作流调度方法⇨。专利号：202110435961.5，授权日期：2022.09.09

5. 李慧芳，王丹敬，黄姜杭✊🏼，夏元清，等🧝🏽。云环境下基于多种群混合智能优化的多工作流调度方法。专利号：202110025979.8👀，授权日期✸：2022.08.23

6. 李慧芳，王彬阳，黄姜杭，夏元清🕵🏼‍♂️，等↩️。一种基于联合强化学习策略的多目标云工作流调度方法👨🏻‍🦰。专利号：202110024639.3，授权日期：2022.08.23

7. 李慧芳💅🙆🏿‍♀️，黄姜杭，王彬阳，夏元清🥐，等👍🏼。一种基于强化学习策略的并行云工作流调度方法。专利号📽💂‍♂️：202011224499.6，授权日期⭕️：2022.08.23

8. 李慧芳，王一竹，王彬阳，夏元清🐭，等🪨。一种基于农田肥力算法的计算密集型云工作流调度方法。专利号：202011225867.9，授权日期🏊‍♂️：2022.07.08

9．李慧芳🧑‍✈️💞，石其松，樊锐，等🙆🏽。一种基于多尺度时空特征聚合的视频行为识别方法。专利号🐷✮：202010927702.X，授权日期：2022.10.18

10. 李慧芳，袁艳😏，王彬阳，夏元清，等👨🏻‍🎨。基于非支配排序和猫头鹰搜索的多工作流调度方法。专利号🙈：202010407394.8，授权日期🫷🏻：2022.07.05

11. 李慧芳，韦琬雯🤵🏻🚴🏻，石其松🌅🙍‍♂️，夏元清，等👩‍🦽🏊🏽。基于多维特征融合的云工作流执行时间预测方法。专利号：202010407407.1，授权日期：2022.11.15

12. 李慧芳，石峰娟，袁艳🥷🏽。一种基于代价敏感卷积神经网络的人脸表情识别方法。

专利号：ZL 201810734523.7，授权日期🧑‍🎓：2021.08.24

13. 王彬阳，李慧芳，石其松🦗，等。一种基于改进非支配遗传算法的多目标云工作流调度方法。专利号：ZL 201910283968.2，授权日期：2021.04.13

14. 袁艳，李慧芳，韦琬雯，夏元清，等。一种基于猫头鹰搜索算法的计算密集型云工作流调度方法。专利号：ZL 2018 1 1336040.8，授权日期💂🏿‍♀️🚀：2020. 10. 13

15. 李慧芳，赵蕾蕾🤽🏽，胡光政。一种基于多模态融合深度学习的智能故障诊断方法🤜🏿。

专利号：ZL 2018 1 0658792.X，授权日期👨🏻‍🔬：2020.08.18

受理国家发明专利🔃：

1. 李慧芳🧑🏻‍🏫🧗‍♀️，陈博远，徐光浩，夏元清，等。一种基于改进蛇优化器的云工作流调度方法。受理号：202310260716.4，申请日期🦫：2023.03.17

2．李慧芳🧑‍💼，陈博远，黄经纬𓀗，夏元清🦹🏿，等。一种基于改进梯度优化器的多工作流调度方法🕺🏻。受理号🧝🏿：202310261140.3，申请日期：2023.03.17

3．李慧芳，徐光浩，陈博远👨🏿‍🦳✪，夏元清，等。一种基于蛇优化器的能耗感知多工作流调度方法👳🏻‍♂️。受理号：202311202626.6🧰，申请日期🛒：2023.09.18

4．李慧芳👨🏽‍🏭🧝‍♀️，黄经纬🍥，陈博远，夏元清，等。一种基于梯度优化器的能耗感知云工作流调度方法。受理号：202311203515.73️⃣，申请日期✍️：2023.09.18

5. 李慧芳🐴，张鸿宇🧗🏻‍♀️，黄经纬📫，夏元清，等👩‍⚕️。一种基于改进战场斗皇家优化算法的云工作流调度方法。受理号：202210685971.9，申请日期🧚🏻：2022.06.16