郭迎亚-5657威尼斯
师资队伍

郭迎亚

来源:     发布日期:2022-09-09    浏览次数:

郭迎亚-5657威尼斯

职称:副教授

职务:硕士生导师

研究方向:人工智能与网络优化,流量工程,路由优化,软件定义网络,边缘计算,网络流量分类和异常监测

电子邮件:guoyy@fzu.edu.cn

郭迎亚,女,博士,副教授,硕士生导师,福建省高层次人才b 类,中国计算机学会互联网专委会执行委员,福建省计算机学会理事。研究方向为计算机网络以及人工智能算法在网络中的应用,具体包括流量工程,软件定义网络,智能路由,边缘计算,物联网,网络流量异常检测。主持参与国家重点研发计划项目、国家863项目、国家自然科学基金项目、福建省自然科学基金、福建省中青年教师教育科研项目等多项国家级和省级科研项目,在ieee international conference on computer communications (infocom)、acm international conference on emerging networking experiments and technologies (conext)、ieee international conference on network protocols (icnp)、ieee/acm transaction on networking (ton)、iieee transactions on mobile computing (tmc)等国家高水平期刊和会议发表论文40余篇,授权国家发明专利3项,担任ieee transactions on parallel and distributed systems (tpds),ieee/acm transaction on networking (ton),journal of network and computer application (jnca),computer networks (cn),ieee/acm international symposium on quality of service (iwqos)等国际会议与期刊的审稿人。跟国内外各大高校,清华大学,浙江大学,中国科学院,香港理工大学,复旦大学,厦门大学,以及国内公司,阿里巴巴,腾讯,华为保持紧密的合作和联系。ainet课题组每年招收2-3名硕士研究生和若干本科生,欢迎对网络和人工智能感兴趣的本科生和硕士生邮件联系我(邮件请附上自己的简历和成绩单)。希望学生具有扎实的计算机和数学基础,较强的写作技能,勤奋努力,性格好。更多信息详见个人5657威尼斯主页:https://yingyaguo.github.io/

1. 本科:计算机科学与技术专业,厦门大学,2009.09-2013.07

2. 博士:计算机科学与技术专业,清华大学,2013.09-2019.07,导师:吴建平院士

3. 博士联合培养:纽约大学,2017.10-2018.09,导师:h. jonathan chao教授

1. 国家自然科学基金青年基金项目,混合软件定义网络下基于深度增强学习的路由优化研究,主持,2021.1-2023.12,已结题

2. 福建省自然科学基金青年项目,基于深度增强学习的混合软件定义网络智能路由方法研究,主持,2020.11-2023.11,已结题

3. 福建省教育厅中青年教师教育科研项目,面向流量工程的互联网智能路由研究,主持,2020.05-2022.05,已结题

  1. 1. siping shi, yingya guo*, dan wang, yifei zhu, zhu han. distributionally robust federated learning for network traffic classification with noisy labels[j]. ieee transactions on mobile computing, 2023, doi: 10.1109/tmc.2023.3319657,1-15. (ccf-a, 中科院一区sci)

  2. 2. han zhang, xia yin, xingang shi*, yingya guo, tian lan, yahui li, and haijun geng. achieving high availability in inter-dc wan traffic engineering [j]. ieee/acm transactions on networking, 2022:1-16. (ccf-a)

  3. 3. ying tian, zhiliang wang*, xia yin, xingang shi, yingya guo, haijun geng and jiahai yang. traffic engineering in partially deployed segment routing over ipv6 network with deep reinforcement learning [j]. ieee/acm transactions on networking, 2020, 28(4): 1573-1586. (ccf-a)

  4. 4. yingya guo, dan wang*. feat: a federated approach for privacy-preserving network traffic classification in heterogeneous environments[j]. ieee internet of things journal, 2022, 10 (2): 1274-1285. (物联网顶刊,中科院一区sci)

  5. 5. yingya guo, yulong ma, huan luo* and jianping wu. traffic engineering in a shared inter-dc wan via deep reinforcement learning[j]. ieee transactions on network science and engineering, 2022, 9(4): 2870-2881. (中科院一区sci)

  6. 6. yingya guo, yufei peng, run hao and xiang tang*. capturing spatial–temporal correlations with attention based graph convolutional network for network traffic prediction[j]. journal of network and computer applications, 2023, 220: 103746. (中科院二区sci)

  7. 7. yingya guo, weipeng wang, han zhang*, wenzhong guo, zhiliang wang, ying tian, xia yin and jianping wu. traffic engineering in hybrid software defined network via reinforcement learning[j]. journal of network and computer applications, 2021,189: 103-116. (中科院二区sci)

  8. 8. yingya guo, zhiliang wang, xia yin, xingang shi and jianping wu. traffic engineering in sdn/ospf hybrid network[c]. ieee international conference on network protocols (icnp) , 2014: 563-568. (ccf-b, 谷歌学术引用次数175)

  9. 9. cheng hu, yingya guo*, yuhui deng, longya lang, et al. improve the energy efficiency of datacenters with the awareness of workload variability[j]. ieee transactions on network and service management, 2022, 19(2): 1260-1273. (中科院二区sci)

  10. 10. han zhang, xingang shi *, xia yin, jilong wang, zhiliang wang, yingya guo, tian lan. boosting bandwidth availability over inter-dc wan[c]. acm international conference on emerging networking experiments and technologies (conext), 2021: 297-312. (ccf-b)

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