Li CHEN - 陈 力
Associate Researcher, Beijing Zhongguancun Laboratory
Many openings for Ph.D students. Drop me an email if interested.
On the Web
Google Scholar |
- [2023-09-30] dRR and our measurement study on ROV deployment are accepted to NDSS with minor revision!
- [2023-09-27] Attended Huawei STW 2023 and presented DONS.
- [2023-09-15] Presented our work on LLM for NetOps in CCF ChinaNet 2023.
- [2023-07-06] Looking for my first batch of Ph.D students!
- [2023-05-18] DONS is accepted to SIGCOMM 2023.
- [2023-04-06] Primus published in IEEE ToN.
- [2023-03-29] Attended SAVNET WG meeting remotely and presented SAVOP in IETF 116 .
- [2023-02-06] GIFT published in IEEE JSAC.
- [2023-02-03] APF published in IEEE TPDS.
- [2023-01-03] Promoted to Associate Researcher at Zhongguancun Laboratory.
- [2022-12-02] Elected to CCF TCI Executive Commitee.
Selected Recent Publications
- [SIGCOMM] Gao, Kaihui, Li Chen, Dan Li, Vincent Liu, Xizheng Wang, Ran Zhang, and Lu Lu. "DONS: Fast and Affordable Discrete Event Network Simulation with Automatic Parallelization." In Proceedings of the ACM SIGCOMM 2023 Conference, pp. 167-181. 2023.
- [SIGCOMM] Chen, Huangxun, Yukai Miao, Li Chen, Haifeng Sun, Hong Xu, Libin Liu, Gong Zhang, and Wei Wang. "Software-defined Network Assimilation: Bridging the Last Mile Towards Centralized Network Configuration Management with NAssim." In Proceedings of the ACM SIGCOMM 2022 Conference, pp. 281-297. 2022.
- [SIGCOMM] Yang, Qingqing, Xi Peng, Li Chen, Libin Liu, Jingze Zhang, Hong Xu, Baochun Li, and Gong Zhang. "DeepQueueNet: Towards Scalable and Generalized Network Performance Estimation with Packet-level Visibility." In Proceedings of the ACM SIGCOMM 2022 Conference, pp. 441-457. 2022.
- [NSDI] Zhao, Yikai, Kaicheng Yang, Zirui Liu, Tong Yang, Li Chen, Shiyi Liu, Naiqian Zheng et al. "LightGuardian: A Full-Visibility, Lightweight, In-band Telemetry System Using Sketchlets." In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21), pp. 991-1010. 2021.
- [SIGCOMM] Chen, Li, Justinas Lingys, Kai Chen, and Feng Liu. "AuTO: Scaling Deep Reinforcement Learning for Datacenter-Scale Automatic Traffic Optimization." In Proceedings of the 2018 conference of the ACM special interest group on data communication, pp. 191-205. 2018.
... View the full list here [bib], or refer to my Google Scholar page, which I keep updated.
MegaSwitch [NSDI'17] |
PowerMan [NSDI'18] |
||Huawei Queueing Theory Workshop
||Tencent-Barefoot P4 Day
|| Associate Researcher, Zhongguancun Laboratory
|| Systems Researcher, Huawei Hong Kong Research Center
|| Senior Engineer, Network Platform Division, TEG, Tencent
|| Certified Instructor, NVIDIA Deep Learning Institute
|| Teaching Assistant, HKUST
||Ph.D. in Computer Science and Engineering
||M.Phil. in Electronic and Computer Engineering
||B.Eng. in Electronic and Computer Engineering
||(with First Class Honors and Minor in Mathematics)
||Exchange student in College of Engineering
||University of Michigan
Awards and Honors
||SIGCOMM Best Paper Award
||Microsoft Research Asia Ph.D. Fellowship
||The Commercial Radio 50th Anniversary Scholarships
||Meritorious Winner of Mathematical Competition of Modeling
||HKUST Scholarship for Continuing UG Students
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