Zaipeng Xie

Zaipeng Xie

Associate Professor, Hohai Univeristy

I am currently an Associate Professor in the Department of Computer Science and Technology at Hohai University, China. I hold a B.Eng. degree in Information Engineering from Southeast University, Nanjing, China, an M.Eng. degree in Electrical Engineering from South China University of Technology, and a Ph.D. degree in Electrical and Computer Engineering from the University of Wisconsin-Madison, USA. I was a visiting scholar at Oak Ridge National Laboratory, USA, from 2009 to 2015. Subsequently, I held the position of Postdoctoral Fellow at the same institution until the end of 2015. My research expertise lies in the fields of Distributed Computing, Machine Learning, and their Applications. I have authored more than 30 papers and have been granted over 10 Invention Patents, exploring the application of these technologies in various domains.

My current research topics include Federated Learning, Multi-agent Reinforcement Learning, and their Applications. I am currently one of the Associate Editors for “Sustainable Computing: Informatics and Systems.”

News in 2024

  • New (05/2024) Our paper has been accepted by the 2024 IEEE 17th International Conference on Cloud Computing (IEEE CLOUD) (CCF C)!
  • New (03/2024) Our paper has been accepted by the 2024 International Joint Conference on Neural Networks (IJCNN) (CCF C)!
  • New (03/2024) Our paper has been accepted by CAAI Transactions on Intelligent Systems (CCF T2)!
  • New (01/2024) Our paper has been accepted by IEEE Internet of Things Journal (SCI JCR Q1)!
  • New (01/2024) Our paper has been accepted by Computer‐Aided Civil and Infrastructure Engineering (SCI JCR Q1)!

News in 2023

  • New (08/2023) Our paper has been accepted by the CAAI Transactions on Intelligence Technology (SCI JCR Q1)!
  • New (08/2023) Our paper has been accepted by the 30th International Conference on Neural Information Processing (ICONIP) (CCF C)!
  • New (08/2023) Our paper has been accepted by the 2023 IEEE Global Communications Conference (GLOBECOM) (CCF C)!
  • New (07/2023) Our paper has been accepted by the 23rd International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP) (CCF C)!
  • New (07/2023) Our paper has been accepted by the 26th European Conference on Artificial Intelligence (ECAI) (CCF B)!
  • New (06/2023) Our two papers have been accepted by IEEE International Conference on Systems, Man, and Cybernetics (SMC) (CCF C)!
  • New (06/2023) Our paper has been accepted by Sensors (SCI JCR Q2)!
  • New (01/2023) Our paper has been accepted by the 56th IEEE International Symposium on Circuits and Systems (ISCAS) (CCF C)!

Recent Publications

  1. Zaipeng Xie*, Han Xu, Xing Gao, Junchen Jiang, and Ruiqian Han. “Fed2PKD: Bridging Model Diversity in Federated Learning via Two-Pronged Knowledge Distillation.” Accepted in 2024 IEEE 17th International Conference on Cloud Computing (IEEE CLOUD), July 7-13, 2024, Shenzhen, China. (CCF-C, Oral presentation)
  2. Jianan Zhang, Zaipeng Xie*, Hongxing Li, Xuanyao Jie, Yunfei Wang, and Bowen Li. “SQMG: An Optimized Stochastic Quantization Method Using Multivariate Gaussians for Distributed Learning.” In 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan. (CCF-C, Poster presentation) [PDF][Slides]
  3. Yingjian Song, Bingnan Li, Dan Luo, Zaipeng Xie, Bradley G Phillips, Yuan Ke, Wenzhan Song. “Engagement-Free and Contactless Bed Occupancy and Vital Signs Monitoring,” in IEEE Internet of Things Journal, vol. 11, no. 5, pp. 7935-7947, 1 March 1, 2024; (SCI JCR Q1) [URL]
  4. Tian Gao, Zhiyuan Yuanzhou, Bohai Ji*, Zaipeng Xie*. “Vision‐based fatigue crack automatic perception and geometric updating of finite element model for welded joint in steel structures.” Computer‐Aided Civil and Infrastructure Engineering (2024); (SCI JCR Q1) [URL]
  5. Zaipeng Xie*, Cheng Ji, Chentai Qiao, WenZhan Song, Zewen Li, Yufeng Zhang, and Yujing Zhang. “MioDSC: Mutual Information Oriented Deep Skill Chaining for Multi-Agent Reinforcement Learning.” CAAI Transactions on Intelligence Technology 1–17(2024); (SCI JCR Q1) [URL][PDF]
  6. Zaipeng Xie*, Ziang Liu, Peng Chen, and Jianan Zhang. “Efficient Spiking Neural Architecture Search with Mixed Neuron Models and Variable Thresholds.” In Proceedings of the 30th International Conference on Neural Information Processing (ICONIP), Nov.20-23, 2023, Changsha, China. (CCF-C, Oral presentation) [URL][PDF]
  7. Zaipeng Xie*, Jianan Zhang, Yida Zhang, Chenghong Xu, Peng Chen, Zhihao Qu, and WenZhan Song. “An Efficient Fault Tolerance Strategy for Multi-task MapReduce Models Using Coded Distributed Computing.” In Proceedings of the 23rd International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), 20-22 October 2023, Tianjin, China. (CCF-C, Oral presentation) [URL][PDF]
  8. Zaipeng Xie*, Wenhao Fang, Bingzhe Yu, Yang Ding, Yanling Pan, and WenZhan Song. “AMTL-Loc: Efficient WiFi Indoor Localization with Reduced Fingerprint Collection.” In Proceedings of 2023 IEEE Global Communications Conference (GLOBECOM), 4–8 December 2023, Kuala Lumpur, Malaysia. (CCF-C, Oral presentation) [URL][PDF]
  9. Jin Lu, Zaipeng Xie*, Jiayu Chen, Maohua Li, Chenghong Xu, and Hongli Cao. “GC-SALM: Multi-Task Runoff Prediction Using Spatial-Temporal Attention Graph Convolution Networks.” In Proceedings of the 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC). October 1-4, 2023, Hyatt Maui, Hawaii, USA. (CCF-C, Oral presentation) [URL][PDF]
  10. Zaipeng Xie*, Yufeng Zhang, Chentai Qiao, and Sitong Shen. “IPERS: Individual Prioritized Experience Replay with Subgoals for Sparse Reward Multi-Agent Reinforcement Learning.” In Proceedings of the 26th European Conference on Artificial Intelligence ECAI 2023 (ECAI), 2-5 October 2023, Kraków, Poland. (CCF-B, Oral presentation) [URL] [PDF]
  11. Wenzhong Wang, Zaipeng Xie*, Bingzhe Yu, Zhihao Qu, Yufeng Zhang, and Hongli Cao. “Federated Learning with Common Representation Learning Criterion and Personalized Predictor.” In Proceedings of the 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC). October 1-4, 2023, Hyatt Maui, Hawaii, USA. (CCF-C, Oral presentation) [URL] [PDF]
  12. Zaipeng Xie* , Cheng Ji, Lifeng Xu, Mingyao Xia, and Hongli Cao. Towards an Optimized Distributed Message Queue System for AIoT Edge Computing: A Reinforcement Learning Approach. Sensors. 2023; 23(12):5447. (SCI JCR Q2) [URL] [PDF]
  13. Zaipeng Xie*, Chenyu Yuan, Likun Li, and Jiahao Wu. “Energy-Efficient Stochastic Computing for Convolutional Neural Networks by Using Kernel-wise Parallelism.” in Proceedings of the 56th IEEE International Symposium on Circuits and Systems (ISCAS), May 21-25, 2023, Monterey, California, USA. (CCF-C, Oral presentation) [URL] [PDF]
  14. Zaipeng Xie*, Junchen Jiang, Ruifeng Chen, Zhihao Qu, and Hanxiang Liu. “FedDGIC: Reliable and Efficient Asynchronous Federated Learning with Gradient Compensation.” in Proceedings of the 28th IEEE International Conference on Parallel and Distributed Systems (ICPADS), January 10-12, 2023. (CCF-C, Oral presentation). [URL] [PDF]
  15. Zaipeng Xie*, Yao Liu, Zhihao Qu, Bin Tang, and Weiyi Zhao. “FedALP: An Adaptive Layer-Based Approach for Improved Personalized Federated Learning.” in Wireless Algorithms, Systems, and Applications: 17th International Conference (WASA), November 24–26, 2022. (CCF-C, Oral presentation) [URL] [PDF]
  16. Zaipeng Xie*, Yufeng Zhang, Pengfei Shao, and Weiyi Zhao. “QDN: An Efficient Value Decomposition Method for Cooperative Multi-agent Deep Reinforcement Learning.” in Proceedings of the 34th International Conference on Tool with Artificial Intelligence (ICTAI), October 31-November 2, 2022. (CCF-C, Oral presentation) [URL] [PDF]
  17. Zaipeng Xie*, Cheng Ji, and Yufeng Zhang. “Deep Skill Chaining with Diversity for Multi-agent Systems.” Artificial Intelligence. CICAI 2022. Lecture Notes in Computer Science, vol 13606. Springer, Cham., Beijing, China, August 27–28, 2022. (Oral presentation, Finalist of Best Student Paper Award) [URL] [PDF]

Granted Invention Patents

  1. (CN107908457B, 2020.03.17), A Containerized Cloud Resource Allocation Method Based on Stable Matching (一种基于稳定匹配的容器化云资源分配方法)
  2. (CN111045843B, 2021.09.28), A Fault-Tolerant Distributed Data Processing Method (具有容错能力的分布式数据处理方法)
  3. (CN112434805A, 2022.08.05), A Deep Neural Network Module Segmentation Method (一种深度神经网络模块分割方法)
  4. (CN112348199A, 2022.08.30), A Model Training Method Based on Federated Learning and Multi-Task Learning (一种基于联邦学习与多任务学习的模型训练方法)
  5. (CN109656713B, 2022.09.16), A Container Scheduling Method Based on Edge Computing Framework (一种基于边缘计算框架的容器调度方法)
  6. (CN113132482B, 2022.10.14), A Distributed Message System Parameter Adaptive Optimization Method Based on Reinforcement Learning (一种基于强化学习的分布式消息系统参数自适应优化方法)
  7. (CN111400026A, 2023.02.28), A Distributed Load Balancing Method Based on Master-Slave Backup Technique (一种基于主从备份技术的分布式负载均衡方法)
  8. (CN111104215A, 2023.03.24), A Stochastic Gradient Descent Optimization Method Based on Distributed Coding (一种基于分布式编码的随机梯度下降优化方法)
  9. (CN112364985A, 2023.07.18), A convolution optimization method based on distributed coding (一种基于分布式编码的卷积优化方法)
  10. (CN109788046B, 2020.06.16), A Multi-Strategy Edge Computing Resource Scheduling Method Based on Improved Bee Algorithm (一种基于改进蜂群算法的多策略边缘计算资源调度方法)
  11. (CN110276728A, 2022.08.05), A Face Video Enhancement Method Based on Residual Generative Adversarial Networks (一种基于残差生成对抗网络的人脸视频增强方法)
  12. (CN112988275B, 2022.10.14), A Task-Aware Mobile Edge Computing Method for Multi-User Computation Offloading (一种基于任务感知的移动边缘计算多用户计算卸载方法)
  13. (CN114269006A, 2023.04.14), An indoor AP clustering selection method and device based on information gain rate (一种基于信息增益率的室内AP聚类选取方法和设备)
  14. Craig E. Deibele, Douglas E. Curry, Richard W. Dickson, Zaipeng Xie, “High speed high dynamic range high accuracy measurement system,” U.S. Patent 9,506,953, Nov 29, 2016.

Teaching

  • 0611026, Introduction to Computational Thinking
  • 0601122, Computer Organization and Architecture
  • 21M070304, Distributed Computing Systems

Contact

If you’re interested in my research, please contact me at zaipengxie@hhu.edu.cn