姓名：高凯
职称：副研究员（专职科研）
电子邮件：kaigao@scu.edu.cn
研究方向：软件定义网络，可编程网络，网络-应用协作
高凯博士2018年于清华大学计算机科学与技术系获工学博士学位，主要的研究方向是软件定义网络、可编程网络和网络-应用协作优化。在国际顶尖的会议、期刊上发表论文多篇，曾担任ACM Computing Surveys、ACM SOSR 2021、ACM SIGCOMM NAI 2020/2021等期刊、会议、研讨会评审，以及ACM SIGCOMM NAI 2021研讨会联席主席。高凯博士同时活跃在IETF的ALTO工作组，领导了ALTO-PV标准草案的制订（该草案目前仍在标准化过程中）。
目前担任下列课程的主讲教师：
1. 国家自然科学基金委员会青年科学基金项目61902266，《面向SDN和NFV融合网络的高级编程基础理论和关键技术研究》
1. Gao, K., Nojima, T., Yu, H. and Yang, Y.R. 2020. Trident: Toward Distributed Reactive SDN Programming With Consistent Updates. IEEE Journal on Selected Areas in Communications. 38, 7 (Jul. 2020), 1322–1334. DOI:https://doi.org/10.1109/JSAC.2020.2999654.(CCF A类期刊, IF=9.144)
2. Gao, K., Nojima, T. and Yang, Y.R. 2018. Trident: Toward a Unified SDN Programming Framework with Automatic Updates. Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication (New York, NY, USA, 2018), 386–401.(CCF A类会议)
3. Gao, K., Xiang, Q., Wang, X., Yang, Y.R. and Bi, J. 2019. An Objective-Driven On-Demand Network Abstraction for Adaptive Applications. IEEE/ACM Transactions on Networking. 27, 2 (2019), 805–818. DOI:https://doi.org/10.1109/TNET.2019.2899905.(CCF A类期刊，IF=3.56)
4. Gao, K., Zhang, J., Yang, Y.R. and Bi, J. 2018. Prophet: Fast Accurate Model-based Throughput Prediction for Reactive Flow in DC Networks. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications (INFOCOM 2018) (Honolulu, USA, Apr. 2018).(CCF A类会议)
5. Gao, K., Xiang, Q., Wang, X., Yang, Y.R. and Bi, J. 2017. NOVA: Towards on-demand equivalent network view abstraction for network optimization. 2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS) (Jun. 2017), 1–10.(CCF B类会议)
6.Zhang, M., Bi, J.,Gao, K., Qiao, Y., Li, G., Kong, X., Li, Z. and Hu, H. 2019. Tripod: Towards a Scalable, Efficient and Resilient Cloud Gateway. IEEE Journal on Selected Areas in Communications. 37, 3 (Mar. 2019), 570–585. DOI:https://doi.org/10.1109/JSAC.2019.2894189.(CCF A类期刊，IF=9.144)
当前位置：