何以凡,男,讲师。2023年毕业于日本筑波大学,并获博士学位,主要研究方向为大语言模型、具身智能、边缘计算、强化学习、演化计算等。目前已在领域内主流国际期刊和会议发表论文10余篇,中科院TOP、CCF-B以上期刊3篇,申请国家发明专利2项。主持浙江省自然科学基金1项,参与日本新能源产业技术综合开发机构(NEDO)项目1项、日本学术振兴会(JSPS)科学研究费助成事业项目2项、浙江省自然科学基金项目1项,主持或参与企业委托横向课题多项。主讲《编译原理》、《数据库原理与应用》等计算机科学、软件工程专业核心课程。
近3年发表论文:
1. Yifan He, Quan Yuan, Jian Lin*, Yiyang Liu, and Mengqing Gan: A Reinforcement Learning-based Hyper-heuristic Evolutionary Algorithmfor Distributed Heterogeneous Fuzzy Flexible Job Shop Scheduling [J]. Expert Systems with Applications. 2026.
2. Yifan He, Zhan Xu, Jian Lin*, Yuanzhuang Li, and Shiyu Zhang: Deep Reinforcement Learning with Evolved Actions for Dynamic Workflow Scheduling in Distributed Fog Computing [J]. Neurocomputing. 2026.
3. 林剑, 徐占, 何以凡*, 许晨昊, 赵治涵: 资源不确定环境下基于深度强化学习的雾计算工作流动态调度优化方法 [J]. 控制与决策. 2026.
4. 林剑, 章诗妤, 彭莉莎*, 何以凡, 李元壮, 徐占: 基于强化学习超启发式算法的混合异构云工作流调度研究 [J]. 计算机集成制造系统. 2026.
5. Jian Lin, Xintao Wang, Rui Niu, and Yifan He*: A Q-Learning-Based Hyper-Heuristic for Capacitated Electric Vehicle Routing Problem [J]. IEEE Transactions on Intelligent Transportation Systems. 2025.
6. Yuanzhuang Li, Yifan He, Jian Lin*, Zhan Xu, and Shiyu Zhang: A Reinforcement Learning-Based Population Hyper-Heuristic for Energy-Efficient Cloud Workflow Scheduling Problem [J]. IEEE Transactions on Services Computing. 2025.
7. Yifan He and Claus Aranha*: Evolving Benchmark Functions to Compare Evolutionary Algorithms via Genetic Programming [C]. 2024 IEEE World Congress on Computational Intelligence (WCCI). 2024.
8. Yongfu Wang, Mingyue Tang, Yifan He, and Tiffany Y. Tang*. Interactive Design with Autistic Children using LLM and IoT for Personalized Training: The Good, The Bad and The Challenging [C]. 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) Companion. 2024.


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