教育与工作经历

郭泽华拥有西北工业大学学士学位、西安电子科技大学硕士学位和西北工业大学博士学位。先后在滴滴出行担任高级软件工程师，蓝汛通信担任研发经理，在美国纽约大学工程学院电气与计算机工程系担任研究员，在美国明尼苏达大学双城分校计算机科学与工程系担任博士后研究员。

研究方向

1. 机器学习系统设计

    主机：轻量化和鲁棒性联邦学习、可扩展分布式机器学习

    网络：在网计算、流量调度

2. 机器学习应用

    强化学习：资源调度、数据中心碳中和

    图神经网络：广域网路由、空天地一体化网络路由

      每年招收2-3名博士或硕士研究生，欢迎计算机、电子、自动化、应用数学专业并致力于网络系统、人工智能以及优化算法相关研究的同学报考，希望考生具有扎实的计算机和数学基础，流利的英语口语和写作技能，勤奋好学，踏实肯干。学生毕业后可根据实际情况推荐至清华、北大、中科院等国内知名高校以及香港、美国、新加坡等国外知名高校继续深造，或推荐至航天5院、华为、中国星网、美团等国内研究所、大型国企、互联网公司工作。

近5年承担的科研项目

承担国家自然科学基金、国家重点研发计划、国家科技支撑计划、北京市自然科学基金、嵩山实验室预研项目、之江实验室开放课题等国家和省部级纵向项目，并与复旦大学、华为、美团、中国铁塔、中国移动开展科研合作，科研项目共计20余项。

代表性学术论文

发表高水平期刊和会议论文100余篇，其中中国计算机协会（CCF）推荐A类和IEEE 会刊30篇，谷歌学术引用2300+，详情请见个人主页https:// guolizihao.github.io/ 和https://scholar.google.com/citations?user= b0bPSfcAAAAJ&hl。

[1] Zehua Guo, Yang Xu, Ya-Feng Liu, et al., AggreFlow: Achieving Power Efficiency, Load Balancing, and Quality of Service in Data Center Networks. IEEE/ACM Transactions on Networking (TON), 2021, vol.29, no.1, pp.17-33. (CCF A)

[2] Zehua Guo, Songshi Dou, Sen Liu, et al., Maintaining Control Resiliency and Flow Programmability in Software-Defined WANs During Controller Failures, IEEE/ACM Transactions on Networking (TON), 2022, vol.30, no.3, pp.969-984. (CCF A)

[3] Zehua Guo, Songshi Dou, Wenchao Jiang, et al., Toward Improved Path Programmability Recovery for Software-Defined WANs under Multiple Controller Failures, IEEE/ACM Transactions on Networking (TON), 2024, vol.32, no.1, pp.143-158. (CCF A)

[4] Zehua Guo, Songshi Dou, Wenfei Wu, et al., Toward Flexible and Predictable Path Programmability Recovery under Multiple Controller Failures in Software-Defined WANs, IEEE/ACM Transactions on Networking (TON), 2023, vol.31, no.5, pp.1965-1980. (CCF A)

[5] Zehua Guo, Jiayu Wang, Sen Liu, et al., SpongeTraining: Achieving High Efficiency and Accuracy for Wireless Edge-assisted Online Distributed Learning, IEEE Transactions on Mobile Computing (TMC), 2023, vol.22, no.8, pp.4930-4945. (CCF A)

[6] Zehua Guo, Weikun Chen, Ya-Feng Liu, et al, Joint Switch Upgrade and Controller Deployment in Hybrid Software-Defined Networks, IEEE Journal on Selected Areas in Communications, 2019, vol.37, no.5, pp.1012-1028. (CCF A)

[7] Zehua Guo, Li Qi, Songshi Dou, et al., Maintaining Control Resiliency for Traffic Engineering in SD-WANs, IEEE/ACM Transactions on Networking, DOI: 10.1109/TNET.2024.3393841. (CCF A)

[8] Songshi Dou, Li Qi, Chao Yao, and Zehua Guo（通信作者）, Exploring the Impact of Critical Programmability on Controller Placement for Software-Defined Wide Area Networks, IEEE/ACM Transactions on Networking (TON), 2023, vol.31, no.6, pp.2575-2588. (CCF A)

[9] Yuntian Zhang, Ning Han, Junjie Zhang, Tengteng Zhu, Minghao Ye, Songshi Dou, and Zehua Guo（通信作者）, Prophet: Traffic Engineering-centric Traffic Matrix Prediction, IEEE/ACM Transactions on Networking (TON), 2024, vol.32, no.1, pp.822-832. (CCF A)

[10] Minghao Ye, Junjie Zhang, Zehua Guo（通信作者）, and H. Jonathan Chao, FlexDATE: Flexible and Disturbance-Aware Traffic Engineering with Reinforcement Learning in Software-Defined Networks, IEEE/ACM Transactions on Networking (TON), 2023, vol.31, no.4, pp.1433-1448. (CCF A).

[11] Minghao Ye, Yang Hu, Junjie Zhang, Zehua Guo（通信作者）, et al., Mitigating Routing Update Overhead for Traffic Engineering by Combining Destination-based Routing with Reinforcement Learning, IEEE Journal on Selected Areas in Communications (JSAC), 2022, vol.40, no.9, pp.2662-2677. (CCF A)

[12] Penghao Sun, Zehua Guo（通信作者）, Junfei Li, et al., Enabling Scalable Network Routing with Deep Reinforcement Learning on Critical Nodes, IEEE/ACM Transactions on Networking (TON), 2022, vol.30, no.2, pp.629-640. (CCF A)

[13] Penghao Sun, Zehua Guo（通信作者）, Junchao Wang, et al., DeepWeave: Accelerating Job Completion Time with Deep Reinforcement Learning-based Inter-Coflow Scheduling, International Joint Conference on Artificial Intelligence 2020 (IJCAI’20). (CCF A)

[14] Junjie Zhang, Minghao Ye, Zehua Guo（通信作者）, et al., CFR-RL: Traffic Engineering with Reinforcement Learning in SDN, IEEE Journal on Selected Areas in Communications (JSAC), 2020, vol.38, no.10, pp 2249-2259. (CCF A)

[15] Minghao Ye, Junjie Zhang, Zehua Guo（通信作者）, et al., LARRI: Learning-based Adaptive Range Routing for Highly Dynamic Traffic in WANs, IEEE International Conference on Computer Communications 2023 (INFOCOM'23). (CCF A)

[16] Songshi Dou, Li Qi, and Zehua Guo（通信作者），ARES: Predictable Traffic Engineering under Controller Failures in SD-WANs, The Web Conference 2024 (WWW’24). (CCF A)

[17] Sen Liu, Yongbo Gao, Zixuan Chen, Jiarui Ye, Haiyang Xu, Furong Liang, Wei Yan, Zerui Tian, Quanwei Sun, Zehua Guo, and Yang Xu, Halflife: An Adaptive Flowlet-based Load Balancer with Fading Timeout in DCN, The European Conference on Computer Systems 2024 (EuroSys’24)}. (CCF A)

[18] Yang Xu, Shikhar Shukla, Zehua Guo, et al., RAPID: Avoiding TCP Incast Throughput Collapse in Public Clouds with Intelligent Packet Discarding. IEEE Journal on Selected Areas in Communications (JSAC), 2019, vol.37, no. 8, pp.1911-1923. (CCF A)

[19] Jiaxin Tang, Sen Liu, Yang Xu, Zehua Guo, et al., ABS: Adaptive Buffer Sizing via Augmented Programmability with Machine Learning, IEEE International Conference on Computer Communications 2022 (INFOCOM’22). (CCF A)

[20] Kuan-yin Chen, Sen Liu, Yang Xu, Ishant Kumar Siddhrau, Siyu Zhou, Zehua Guo, et al., SDNShield: NFV-Based Defense Framework Against DDoS Attacks on SDN Control Plane, IEEE/ACM Transactions on Networking (TON), 2022, vol.30, no.1, pp.1-17. (CCF A)

[21] Songshi Dou and Zehua Guo（通信作者）, Path Programmability Recovery under Controller Failures for SD-WANs: Recent Advances and Future Research Challenges, IEEE Communications Magazine, 2024.

[22] Zehua Guo, Hao Wang, Yi Cai, et al., Analysis and Management of Network Function States, IEEE Network, 2023, vol.37, no.2, pp.206-212.

[23] Ziyong Li, Yuxiang Hu, Jiangxing Wu, Tao Hu, and Zehua Guo（通信作者）, Building Scalable and Flexible Virtual Networks on Programmable Data Plane, IEEE Network, 2024, vol.38, no.2, pp.193-201.

[24] Haowen Zhu, Wenchao Jiang, Qi Hong, and Zehua Guo（通信作者）,When In-Network Computing Meets Distributed Machine Learning, IEEE Network, 2024, DOI: 10.1109/MNET.2024.3368138.

[25] Zehua Guo, Jiayu Wang, Sen Liu, et al, Congestion-aware Critical Gradient Scheduling for Distributed Machine Learning in Data Center Networks, IEEE Transactions on Cloud Computing (TCC), 2023, vol.11, no.3, pp.2296-2311.

[26] Zehua Guo, Songshi Dou, Yi Wang, et al., HybridFlow: Achieving Load Balancing in Software-Defined WANs with Scalable Routing, IEEE Transactions on Communications (TCOM), 2021, vol.8, pp.5255-5268.

[27] Zehua Guo, Changlin Li, Yang Li, et al., Maintaining the Network Performance of Software-Defined WANs with Efficient Critical Routing, IEEE Transactions on Network and Service Management (TNSM), 2024, vol.21, no.2, pp.2240-2252.

[28] Penghao Sun, Julong Lan, Yuxiang Hu, Zehua Guo（通信作者）, et al., Realizing the Carbon-aware Service Provision in ICT System, IEEE Transactions on Network and Service Management (TNSM), 2024, DOI: 10.1109/TNSM.2024.3385484.

[29] Quan Ren, Zehua Guo（通信作者）, Jiangxing Wu, et al., SDN-ESRC: A Secure and Resilient Control Plane for Software-Defined Networks, IEEE Transactions on Network and Service Management (TNSM), 2022, vol.19, no.3, pp.2366-2381.

[30] Tao Wang, Zehua Guo（通信作者）, Hongchang Chen, et al., BWManager: Mitigating Denial of Service Attacks in Software-Defined Networks through Bandwidth Prediction, IEEE Transactions on Network and Service Management (TNSM), 2018, vol.15, no. 4, pp.1235-1248.

授权国家发明专利及出版专著

专利

1. 基于强化学习的数据中心网络能耗和服务质量优化方法，专利号：ZL202010308862.6.

2. 软件定义网络中多控制器失效时流的可编程性优化方法，专利号：ZL202010544094.4.

3.一种软件定义广域网中实现负载均衡的可扩展路由方法，专利号：ZL202010974299.6.

4. 生成心理声学模型的方法及装置，专利号：ZL201010123999.0.

5. 基于图神经网络深度强化学习的多coflow调度方法，专利号：ZL202010501622.8.

6. 一种在软件定义网络中实现控制器负载均衡的方法，专利号：ZL202010094237.6.

7. 一种以流量工程为中心的流量矩阵预测方法，专利号：ZL202110810615.0.

8. 一种基于在线联邦学习的图像分类方法，专利号：ZL202011630474.6.

9. 一种可防御拜占庭攻击的联邦学习图像分类方法，专利号：ZL202110245686.0.

10. 一种智慧操场中的计数方法、系统及装置，专利号：ZL202110793868.1.

11.一种基于模型分解的分布式机器学习模型传输压缩方法，申请号：202211123168.2.

12. 一种容错控制方法、装置及容错构件，申请号：201810368148.9.

专著

1. Bringing Machine Learning to Software-Defined Networks, Springer Nature, 2022, 1-68.

2. Chapter 5: Machine learning models for sensory data analytics, Empowering IoT with Big Data Analytics, Elsevier, 2024.

科研获奖

1. 2023年小米青年学者

2. 2023年中国电子学会物联网专家委员会优秀期刊论文

3. 2023年yl34511线路中心教书育人类表彰

4. 2022年中国电子学会优秀硕士学位论文指导教师

5. 2022年入选斯坦福大学全球前2%顶尖科学家榜单

6. 2022年北京市普通高校优秀本科毕业设计（论文）指导教师

7. 2022年yl34511线路中心优秀硕士学位论文指导教师

8. 2022年yl34511线路中心教书育人类表彰

9. 2021年入选斯坦福大学全球前2%顶尖科学家榜单

10. 2021年ACM SIGCOMM China 新星奖（全国唯一）

11. 2021年北京市普通高校优秀本科毕业设计（论文）指导教师

12. 2021年河南省统计科学研究优秀课题一等奖

13. 2017年西北工业大学优秀博士毕业论文

讲授课程、出版教材及教学成果

讲授课程

1. 计算机网络与分布式计算

2. 工程经济学

出版教材

教学成果

指导学生科技创新获奖

1. 2024yl34511线路中心科技创新计划特立学生科技创新团队

2. 2023yl34511线路中心工程硕博士实践创新能力提升专项计划卓越基金

3. 2023年研究生国家奖学金

4. 2023年北京地区高等学校优秀（硕士）毕业生

5. 2023年yl34511线路中心优秀（硕士）毕业生

6. 2023年挑战杯全国大学生课外学术科技作品竞赛校内特等奖

7. 2022年研究生国家奖学金

8. 2022年中国电子学会优秀硕士学位论文

9. 2022年北京市普通高校优秀本科毕业设计（论文）

10. 2022年yl34511线路中心优秀（硕士）毕业生

11. 2022年yl34511线路中心优秀（本科）毕业生

12. 2022yl34511线路中心本科生校级毕业设计（论文）重点项目

13. 2022年MathorCup高校数学建模挑战赛国家一等奖

14. 2022年MathorCup高校数学建模挑战赛Gurobi创新应用奖国家一等奖

15. 2021年研究生国家奖学金

16. 2021年北京市普通高校优秀本科毕业设计（论文）

学术兼职

1. IEEE Senior Member、IEEE ComSoc Senior Member、IEEE CS Senior Member

2. 中国计算机学会高级会员、互联网专委会执行委员、网络与数据通信专委会执行委员

3. 中国电子学会高级会员、物联网专委会青年专技组委员

4. 中国通信学会高级会员、量子计算委员会委员

5. 中国人工智能学会会员、智能信息网络专委会委员

6. 中国自动化学会会员

7. ACM Member、ACM SIGCOMM Member、ACM SIGCOMM China Member

8. 欧洲信号处理协会会员

9. 期刊编委：IEEE Systems Journal、Springer Telecommunication Systems、EURASIP JWCN、KSII TIIS、电子与信息学报、JPDC

10. TPC：AAAI、IEEE ICDCS、IEEE/ACM IWQoS、IEEE ICCCN、IEEE ICA3PP、IEEE GLOBECOM、IEEE ICC、IEEE ICPADS、ITC…

11. 期刊审稿人：IEEE COMST、IEEE JSAC、IEEE/ACM TON、IEEE TPDS、IEEE TMC、IEEE TCOM、IEEE TNSM、IEEE TCC、IEEE COMMSG、IEEE Network、IEEE IoT、IEEE COMML、IEEE Sensors Journal、COMNET、COMCOM、FGCS、JNCA…

12. 会议审稿人：AAAI、IEEE/ACM IWQoS、IEEE ICPP、IEEE ICPADS、IEEE ICCCN、IEEE GLOBECOM、IEEE ICC、IEEE ISCC、ACM MSWiM、IEEE HPSR、IEEE TENSYMP、IFIP Networking、IEEE TrustCom、ACM CHANTS…

13. 分会主席：IEEE ICPADS 2021、IEEE/ACM IWQoS 2021、IJCAI 2020、IEEE ICC 2018