1.个人简介
陈群健，博士，2024年12月毕业于北京理工大学，2024年12月入职东莞理工学院，主要研究方向包括云边协同、多任务优化、资源调度。近年来，在顶级国际期刊与知名国际会议上发表多篇学术论文，担任IEEE TGCN、IoT-J、TNSE等多个重要期刊的审稿人。
2.联系交流
邮箱：chenqunjian@dgut.edu.cn，欢迎感兴趣的同学们与我沟通，共同开展研究，包括但不限于以下研究方向：
面向工业互联网的云边协同计算
人工智能驱动的优化与调度
大语言模型辅助的算法设计
3.工作经历
2024/12-至今，东莞理工学院，计算机科学与技术学院，准聘讲师
4.主要学术成果
[1] Yang C, Chen Q, Zhu Z, Huang Z A, Lan S, Zhu L. Evolutionary Multitasking for Costly Task Offloading in Mobile-Edge Computing Networks. IEEE Transactions on Evolutionary Computation, 2024, 28(2): 338-352.
[2] Chen Q, Yang C, Lan S, Zhu L, Zhang Y. Two-Stage Evolutionary Search for Efficient Task Offloading in Edge Computing Power Networks. IEEE Internet of Things Journal, 2024: 11(19): 30787-30799.
[3] Q Chen, X Ma, Y Yu, Y Sun, and Z Zhu. Multi-objective evolutionary multi-tasking algorithm using cross-dimensional and prediction-based knowledge transfer. Information Sciences, vol. 586, pp. 540-562, 2022.
[4] Zhang J, Li X, Chen Q, Tao M. Online-Learning Based Task Scheduling in Industrial Internet-of-Things: Tackling Resource Skew with Dynamic Optimization. The 18th International Conference on Knowledge Science, Engineering and Management, August 4-7, Macao, 2025.
[5] Z Chen, M Tao, R Xie, H Nie and Q Chen. MDP-EEC: Model Distillation and Partitioning enhanced End-Edge Collaboration Computing for Consumer Electronics. IEEE Transactions on Consumer Electronics, 2025.
[6] X Ma, Q Chen, Y Yu, Y Sun, L Ma and Z Zhu. A two-level transfer learning algorithm for evolutionary multitasking. Frontiers in Neuroscience, vol. 13, article no. 1408, 2020.
[7] Q Chen, X Ma, Z Zhu, and Y Sun. Evolutionary multi-tasking single-objective optimization based on cooperative coevolutionary memetic algorithm. The 13th International Conference on CIS, December 15-18, Hong Kong, 2017.
[8] Q Chen, X Ma, Y Sun, and Z Zhu, Adaptive memetic algorithm based evolutionary multi-tasking single-objective optimization. The 11th International Conference on SEL, November 10-13, Shenzhen, China, 2017.
