| 姓名： | 屈志昊 | 性别： | 男 | 出生年月： | 1989年01月 |
职称： | 副教授 | 毕业学校： | 南京大学 | |||
专业： | 计算机科学与技术 | 学位： | 博士 | |||
联系电话： |
| 电子邮件： | quzhihao@hhu.edu.cn | |||
研究方向： | 边缘计算、边缘智能、联邦学习 | |||||
个人简介： | 屈志昊，2018年博士毕业于南京大学计算机科学与技术系， 2018年12月-2020年1月在香港理工大学做访问研究员，2019年4月至2021年10月受聘为河海大学计算机与信息学院博士后，2021年11月破格特评为河海大学计算机与信息学院副研究员/副教授。主要从事边缘计算、边缘智能、联邦学习等方向研究，主持国家自然科学基金青年基金、江苏省青年基金、中国博士后二等资助、国网公司科技项目等，作为核心成员参与国家自然科学基金重点项目“基于边缘计算的云端融合理论方法与关键技术研究”、深圳市基础研究专项重点项目“云边端协同学习架构与关键优化理论研究”，香港Research Impact Funding 项目“边缘学习：云端和边缘融合环境中分布式大数据分析实现技术”。在IEEE TMC、IEEE JSAC、IEEE TC、IEEE TPDS、IEEE INFOCOM、DAC、ATC、ICPP 等国际知名期刊和会议上发表论文20余篇。在学术任职与服务方面，屈志昊是CCF会员，IEEE会员，担任IEEE ICPADS 2020出版主席，IEEE Globecom 2022、WASA 2021、IEEE ICFC 2020程序委员会成员，Frontiers in Space Technologies-Aerial and Space Networks审稿编辑（2020年）。参与设计开发的脊大夫无创伤脊柱三维评估系统获得第二届上海交大-卫宁健康智慧医疗挑战赛一等奖（排名第二）。 | |||||
主要成果： | 欢迎对联邦学习，边缘智能，深度学习，基于机器学习的边缘资源优化和网络优化等研究方向感兴趣的同学与我联系。 专著： 1. Song Guo, Zhihao Qu, Edge Learning for Distributed Big Data Analytics: Theory, Algorithms, and System Design, Cambridge University Press, 2022. (ISBN: 9781108832373) 期刊论文(* indicates that I am the corresponding author)： 1. Zhihao Qu, Song Guo, Haozhao Wang, Baoliu Ye, Yi Wang, Albert Y. Zomoya, and Bin Tang, “Partial Synchronization to Accelerate Federated Learning over Relay-Assisted Edge Networks,” IEEE Transactions on Mobile Computing (CCF A类期刊), Preprint, 2021. 2. Jie Zhang, Song Guo, Zhihao Qu*, Deze Zeng, Yufeng Zhan, Qifeng Liu, and Rajendra A. Akerkar “Adaptive Federated Learning on Non-IID Data with Resource Constraint,” IEEE Transactions on Computers (CCF A类期刊), Preprint, 2021. 3. Haozhao Wang, Zhihao Qu, Song Guo, Ningqi Wang, Ruixuan Li, and Weihua Zhuang, “LOSP: Overlap Synchronization Parallel with Local Compensation for Fast Distributed Training,” IEEE Journal on Selected Areas in Communications (CCF A类期刊), vol. 39, no. 8, pp. 2541-2557, Aug. 2021. 4. Haozhao Wang, Song Guo, Zhihao Qu, Ruixuan Li, and Ziming Liu, “Error-Compensated Sparsification for Communication-Efficient Decentralized Training in Edge Environment,” IEEE Transactions on Parallel and Distributed Systems (CCF A类期刊), vol. 33, no. 1, pp. 14-25, Jan. 2022. 5. Qihua Zhou, Song Guo, Zhihao Qu, Peng Li, Li Li, Minyi Guo, and Kun Wang, “Petrel: Heterogeneity-aware Distributed Deep Learning via Hybrid Synchronization,” IEEE Transactions on Parallel and Distributed Systems (CCF A类期刊), vol. 32, no. 5, pp. 1030-1043, 2021. 6. Haozhao Wang, Song Guo, Bin Tang, Ruixuan Li, Chengjie Li, Yutong Yang, Zhihao Qu, “Heterogeneity-aware Gradient Coding for Tolerating and Leveraging Stragglers,” IEEE Transactions on Computers (CCF A类期刊), 2021, Preprint. 7. Jie Zhang, Zhihao Qu*, Chenxi Chen, Haozhao Wang, Yufeng Zhan, Baoliu Ye and Song Guo, “Edge Learning: The Enabling Technology for Distributed Big Data Analytics in the Edge,” ACM Computing Surveys (中科院1区期刊，影响因子10.282), vol. 54, no. 7, pp. 1-36, 2021. 8. Haozhao Wang, Zhihao Qu*, Qihua Zhou, Haobo Zhang, Boyuan Luo, Song Guo, and Ruixuan Li, “A Comprehensive Survey on Training Acceleration for Large Machine Learning Models,” Internet of Things Journal (中科院1区期刊，影响因子9.936), vol. 9, no. 2, pp. 939-963, 2022. 9. Qihua Zhou, Zhihao Qu*, Song Guo, Boyuan Luo, Jingcan Guo, Zhenda Xu, Rajendra Akerkar, “On-device Learning Systems for Edge Intelligence: A Software and Hardware Synergy Perspective,” IEEE Internet of Things Journal (中科院1区期刊，影响因子9.936), vol. 8, no. 15, pp. 11916-11934, 2021. 10. Yufeng Zhan, Peng Li, Song Guo, Zhihao Qu, Incentive Mechanism Design for Federated Learning: Challenges and Opportunities, IEEE Networks (中科院1区期刊，影响因子10.125), vol. 35, no. 4, pp. 310-317, 2021. 11. Zhihao Qu, Baoliu Ye, Bin Tang, Song Guo, Sanglu Lu, and Weihua Zhuang, “Cooperative Caching for Multiple Bitrate Videos in Small Cell Edges,” IEEE Transactions on Mobile Computing (CCF A类期刊), vol. 19, no. 2, pp. 288-299, 2020. 12. Yue Zeng, Baoliu Ye, Bin Tang, Songtao Guo, Zhihao Qu, “Scheduling Coflows of Multi-Stage Jobs under Network Resource Constraints,” Computer Networks (CCF B类期刊), vol. 184, 2020. 13. Tao Huang, Bin Tang, Baoliu Ye, Zhihao Qu, and Sanglu Lu, “Rateless802.11: Extending WiFi Applicability in Extremely Poor Channels”, Computer Networks (CCF B类期刊), vol. 179, no. 9, 2020. 14. Yufeng Zhan, Peng Li, Zhihao Qu, Deze Zeng, and Song Guo, “A Learning-based Incentive Mechanism for Federated Learning,” IEEE Internet of Thing Journal (中科院1区期刊，影响因子9.936), vol. 7, no. 7, 2020. 15. Haozhao Wang, Zhihao Qu, Song Guo, Xin Gao, Ruixuan Li, Baoliu Ye, “Intermittent Pulling with Local Compensation for Communication-Efficient Distributed Learning,” IEEE Transactions on Emerging Topics in Computing, 2020, Preprint.
会议论文(* indicates that I am the corresponding author)： 1. Feijie Wu, Shiqi He, Song Guo, Zhihao Qu*, Haozhao Wang, Weihua Zhuang, Jie Zhang, “Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression,” in Proc. ofDesign Automation Conference (DAC) (CCF A类会议), 2022, Accepted. 2. Qihua Zhou, Song Guo, Zhihao Qu, Jingcai Guo, Zhenda Xu, Jiewei Zhang, Tao Guo, Boyuan Luo, and Jingren Zhou, “Octo: INT8 Training with Loss-aware Compensation and Backward Quantization for Tiny On-device Learning” in Proc. of USENIXAnnual Technical Conference (USENIX ATC) (CCF A类会议), 2021. 3. Ninghui Jia, Zhihao Qu* and Baoliu Ye, “Communication-efficient Federated Learning via Quantized Clipped SGD,” in Proc. of the 16th International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2021. 4. Lin Qian, Baoliu Ye, Xiaoliang Wang, Zhihao Qu, Weiguo Duan, and Ming Zhao, “FastCache: A Client-Side Cache With Variable-Position Merging Schema in Network Storage System,” in Proc. of International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), 2021. 5. Tao Huang, Baoliu Ye, Zhihao Qu, Bin Tang, Lei Xie, and Sanglu Lu, “Physical-Layer Arithmetic for Federated Learning in UL MU-MIMO Enabled Wireless Networks,” in Proc. of International Conference on Computer Communications (INFOCOM) (CCF A类会议), 2020. 6. Lei Zhang, Zhihao Qu*, Baoliu Ye and Bin Tang, “Joint Service Placement and Computation Offloading in Mobile Edge Computing: An Auction-based Approach,” in Proc. of the 26th IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2020. 7. Yamei Dong, Bin Tang, Baoliu Ye, Zhihao Qu and Sanglu Lu, “Intermediate Value Size Aware Coded MapReduce,” in Proc. of the 26th IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2020. 8. Jie Zhang, Song Guo, Deze Zeng, Zhihao Qu, “Multi-path Routing Oriented Flow Statistics Collection in Software Defined Networks,” in Proc. of the 25th IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2019. 9. Zhihao Qu, Baoliu Ye, Bin Tang, Sanglu Lu, and Song Guo, “Energy-aware Cost-effective Cooperative Mobile Streaming on Smartphone Over Hybrid Wireless Networks,” in Proc. of the 44th International Conference on Parallel Processing (ICPP) (CCF B类会议), 2015. 10. Zhihao Qu, Baoliu Ye, Bin Tang, and Sanglu Lu, “Fast Cooperative Content Distribution over Hybrid Wireless Networks,” in Proc. of IEEE Global Telecommunication Conference (GLOBECOM), 2015. | |||||
在研项目： | 1. 国家自然科学基金青年基金，面向无梯度联邦学习的训练加速技术，No. 62102131，2022.1~2024.12，主持。 2. 江苏省自然科学基金青年基金项目，面向边缘智能的联邦学习性能优化技术研究，No. BK20210361， 2021.7~2024.6，主持。 3. 中国博士后基金（二等资助），面向移动VR全景视频的边缘资源协同优化技术研究，No. 2019M661709，2020.1~2021.10，主持。 4. 南京大学软件新技术国家重点实验室开放课题，面向边缘环境的联邦学习训练加速技术研究，No. KFKT2021B11，主持。 5. 中央高校业务费，基于端边云协同的分布式学习关键技术研究，No. B210201053，2021.01~2022.12，主持。 6. 南瑞集团科技项目，边缘侧低可信环境下终端设备安全信任度度量技术研究，2021.07~2021.12，主持。 7. 国家电网科技项目，基于零信任的电力监控系统网络安全准入关键技术研究及装备研制，2022.01~2023.12，河海大学课题负责人。 | |||||
个人主页： | https://jszy.hhu.edu.cn/qzh2/ | |||||
