个人简介
Bingdong Li is currently an associate researcher with the Intelligent Learning and Optimization Group (ILOG), the Shanghai Institute of AI for Education, and the School of Computer Science and Technology, East China Normal University (ECNU), Shanghai, China. He received his B.Sc. and Ph.D. degrees in the School of Computer Science and Technology from University of Science and Tech- nology of China (USTC) in 2011 and 2017, respectively. His research interests include evolutionary computation, machine learning, and their applications. He has published a series of papers in top journals and international conferences. He has served as a reviewer for top-tier journals (TEVC, TETCI).
教育经历
博士：中国科学技术大学计算机科学与技术学院
本科：中国科学技术大学计算机科学与技术学院
工作经历
2021.10-今 华东师范大学计算机科学与技术学院
2019.11-2021.9 美团 算法策略
2017.7-2019.11 腾讯 应用研究
荣誉及奖励
2017 校优秀毕业生
2016 中国科学院院长优秀奖
近期论文
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Bingdong Li, Jinlong Li*, Ke Tang, and Xin Yao. Many-objective evolutionary algorithms: A survey. ACM Computing Surveys (CSUR), IF 7.99, 48(1):13, 2015. (SCI一区, ESI高引用论文)
Bingdong Li, Ke Tang*, Jinlong Li, and Xin Yao. Stochastic ranking for many-objective optimization. Evolutionary Computation, IEEE Transactions on Evolutionary Computation (TEVC), IF 11.169, 2016. (SCI一区)
Bingdong Li, Jinlong Li, Ke Tang, and Xin Yao. An improved two archive algorithm for many-objective optimization. In Evolutionary Computation (CEC), 2014 IEEE Congress on, pages 2869--2876. IEEE, 2014.
Bingdong Li, Chao Qian, Jinlong Li, Ke Tang, and Xin Yao. Search based recommender system using many-objective evolutionary algorithm. In Evolutionary Computation (CEC), 2016 IEEE Congress on. IEEE, 2016.
Hao Hao, Shuai Wang, Bingdong Li and Aimin Zhou*, A Surrogate Model Assisted Estimation of Distribution Algorithm with Mutil-acquisition Functions for Expensive Optimization, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022, pp. 1-8, doi: 10.1109/CEC55065.2022.9870436.
Shuai Wang, Aimin Zhou*, Bingdong Li, and Peng Yang, Differential evolution guided by approximated Pareto set for multiobjective optimization, Information Sciences, Volume 630, 2023, Pages 669-687, https://doi.org/10.1016/j.ins.2023.02.043 (SCI一区)
Shuai Wang, Bingdong Li, and Aimin Zhou*, A regularity augmented evolutionary algorithm with dual-space search for multiobjective optimization, Swarm and Evolutionary Computation, Volume 78, 2023, 101261, https://doi.org/10.1016/j.swevo.2023.101261 (SCI一区)
Bingdong Li, Yan Zhang, Peng Yang, Xin Yao, and Aimin Zhou*, A Two-Population Algorithm for Large-Scale Multi-objective Optimization Based on Fitness-Aware Operator and Adaptive Environmental Selection, IEEE Transactions on Evolutionary Computation, doi: 10.1109/TEVC.2023.3296488 (SCI一区)
Yongfan Lu, Bingdong Li*, Hong Qian, Wenjing Hong, Peng Yang, and Aimin Zhou, RM-SAEA: Regularity Model Based Surrogate-Assisted Evolutionary Algorithms for Expensive Multi-Objective Optimization GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference. 2023: 722-730. (CCF-C)
Yongfan Lu, Bingdong Li*, Shengcai Liu, and Aimin Zhou, A Population Cooperation based Particle Swarm Optimization algorithm for large-scale multi-objective optimization, Swarm and Evolutionary Computation, Volume 83, 2023, 101377, ISSN 2210-6502. (SCI一区)
Yan Zhang, Bingdong Li*, Wenjing Hong, and Aimin Zhou, MOCPSO: A multi-objective cooperative particle swarm optimization algorithm with dual search strategies, Neurocomputing, 2023, 126892, ISSN 0925-2312. (SCI二区)
Bingdong Li, Yongfan Lu, Hong Qian, Wenjing Hong, Peng Yang, Aimin Zhou, Regularity model based offspring generation in surrogate-assisted evolutionary algorithms for expensive multi-objective optimization, Swarm and Evolutionary Computation, Volume 86, 2024, 101506 (SCI一区)
Yongfan Lu, Bingdong Li*, and Aimin Zhou, Are You Concerned about Limited Function Evaluations: Data-Augmented Pareto Set Learning for Expensive Multi-Objective Optimization，Proceedings of the AAAI Conference on Artificial Intelligence. 2024, 38(13): 14202-14210. (CCF-A)
Bingdong Li, Yanting Yang, Dacheng Liu, Yan Zhang, Aimin Zhou?, Xin Yao, Accelerating Surrogate Assisted Evolutionary Algorithms for Expensive Multi-Objective Optimization via Explainable Machine Learning,2024, Swarm and Evolutionary Computation, accepted. (SCI一区)
Bingdong Li, Yanting Yang, Wenjing Hong, Peng Yang, and Aimin Zhou*, Hyperbolic Neural Network Based Preselection for Expensive Multi-Objective Optimization, 2024, IEEE Transactions on Evolutionary Computation, accepted. (SCI一区)
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