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Liekang Zeng Ph.D. Institute of Advanced Networking and Computing Systems School of Computer Science and Engineering Sun Yat-sen University No. 132, Outer Ring East Road, Panyu, Guangzhou, China E-mail: zenglk3 [AT] mail2 [dot] sysu [dot] edu [dot] cn My GitHub, dblp, and Google Scholar [>2000 citations] |
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Biography
I obtained my Ph.D. degree (with honor) at School of Computer Science and Engineering, Sun Yat-sen University, supervised by Prof. Xu Chen. Before that, I received my B.E. degree (with honor) at School of Data and Computer Science, Sun Yat-sen University.
Research Interests
My research interest lies in building full-stack edge intelligence systems with real-time responsiveness, systematic resource efficiency, and theoretical performance guarantee.
Currently, I focus on developing efficient and affordable LLM and graph learning systems with distributed edge computing.
Research Overview:
- Collaborative Edge Intelligence 🌟[project page]
- Edge Robotics
- Edge Network Optimization
- Satellite edge computing: SECO [INFOCOM '24]
- Sustainable federated learning systems: FlocOff [JSAC '24], HERO [IOTM '24]
- Efficient edge offloading: MOGR [ICC '24], IAO [IoTJ '21], CERP [RTSS '19]
- Practical privacy and security: ChainDP [IWQoS '23]
- Definition and taxonomy of edge intelligence: Review [PIEEE '19]
News
- 🆕 [May 2024] Our project homepage of Collaborative Edge Intelligence has been officially launched. Check it out!
- 🆕 [May 2024] One paper on data heterogeneity resilient federated learning is accepted by JSAC. Congrats, Mulei!
- [May 2024] One paper on edge service localization is accepted by DTMTDCS workshop (in conjunction with ICDCS'24). Congrats, Chenyu!
- [Apr. 2024] One paper on the vision of collaborative edge computing for LLMs is accepted by IEEE Wireless Communications.
- [Apr. 2024] One paper on energy-efficient federated learning is accepted by IEEE Internet of Things Magazine. Congrats, Chenyu!
- [Apr. 2024] Awarded as the Excellent Reviewer of IEEE TNSE by IEEE Communications Society.
- [Feb. 2024] One paper on cluster data analysis is accepted by ICCN workshop (in conjunction with INFOCOM'24). Congrats, Chenyu!
- [Jan. 2024] One paper on GNN-assisted task offloading is accepted by ICC'24. Congrats, Mulei!
- [Dec. 2023] Two papers on edge-enabled efficient Transformer inference and satellite edge computing for earth observation missions are accepted to INFOCOM'24. Congrats, Shengyuan and Zhiwei!
- [Nov. 2023] One paper on efficient DNN training with heterogeneous edge devices is conditionally accepted by MobiCom'24. Congrats, Shengyuan!
- [July 2023] One paper on autonomous edge-assisted drone navigation is accepted by TON. ...
Selected Publication
Full Publication, + indicates equal contribution, * indicates corresponding author, ^ indicates the student mentored by me.
- Implementation of Big AI Models for Wireless Networks with Collaborative Edge Computing.
[paper] [bibtex]
Liekang Zeng, Shengyuan Ye, Xu Chen, Yang Yang.
IEEE Wireless Communications, 2024. - FlocOff: Data Heterogeneity Resilient Federated Learning with Communication-Efficient Edge Offloading.
[paper]
[bibtex]
Mulei Ma^, Chenyu Gong^, Liekang Zeng*, Yang Yang, Liantao Wu.
IEEE Journal of Selected Areas in Communications (JSAC), 2024. CCF-A. - Galaxy: A Resource-Efficient Collaborative Edge AI System for In-Situ Transformer Inference.
[paper]
[slides]
[demo]
[bibtex]
Shengyuan Ye^, Jiangsu Du, Liekang Zeng, Wenzhong Ou, Xiaowen Chu, Yutong Lu, Xu Chen.
IEEE International Conference on Computer Communications (INFOCOM), 2024. CCF-A. - SECO: Multi-Satellite Edge Computing Enabled Wide-Area and Real-Time Earth Observation Missions.
[paper]
[slides]
[bibtex]
Zhiwei Zhai^, Liekang Zeng, Tao Ouyang, Shuai Yu, Qianyi Huang, Xu Chen.
IEEE International Conference on Computer Communications (INFOCOM), 2024. CCF-A. - Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices.
[paper] [bibtex]
Shengyuan Ye+^, Liekang Zeng+, Xiaowen Chu, Guoliang Xing, Xu Chen.
ACM International Conference on Mobile Computing and Networking (MobiCom), 2024. CCF-A. - A3D: Adaptive, Accurate and Autonomous Navigation for Edge-Assisted Drones.
[paper] [bibtex]
Liekang Zeng, Haowei Chen^, Daipeng Feng^, Xiaoxi Zhang, Xu Chen.
IEEE/ACM Transactions on Networking (TON), 2023. CCF-A. - Serving Graph Neural Networks with Distributed Fog Servers for Smart IoT Services.
[paper] [bibtex]
Liekang Zeng, Xu Chen, Peng Huang^, Ke Luo, Xiaoxi Zhang, Zhi Zhou.
IEEE/ACM Transactions on Networking (TON), 2023. CCF-A. - GNN at the Edge: Cost-Efficient Graph Neural Network Processing over Distributed Edge Servers.
[paper] [bibtex] [blog]
Liekang Zeng, Chongyu Yang^, Peng Huang^, Zhi Zhou, Shuai Yu, Xu Chen.
IEEE Journal of Selected Areas in Communications (JSAC), 2022. CCF-A. - Fograph: Enabling Real-Time Deep Graph Inference with Fog Computing.
[paper] [slides] [video] [bibtex] [blog]
Liekang Zeng, Peng Huang^, Ke Luo, Xiaoxi Zhang, Zhi Zhou, Xu Chen.
The Web Conference (WWW), 2022. CCF-A, AR=17.7%. - CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices.
[paper] [bibtex]
Liekang Zeng, Xu Chen, Zhi Zhou, Lei Yang, Junshan Zhang.
IEEE/ACM Transactions on Networking (TON), 2021. CCF-A.
🏵️ Recognized in TON's Top 5 popular articles (Dec. 2021 - Oct. 2022). - Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing.
[paper] [bibtex] [press-ABI Research]
En Li+, Liekang Zeng+, Zhi Zhou, Xu Chen.
IEEE Transactions on Wireless Communications (TWC), 2020. CCF-B.
🔥 ESI Highly Cited Paper (500+ Citations). - Boomerang: On-Demand Cooperative Deep Neural Network Inference for Edge Intelligence on the Industrial Internet of Things.
[paper] [bibtex] [press-ABI Research]
Liekang Zeng, En Li, Zhi Zhou, Xu Chen.
IEEE Network (NET), 2019. - Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing.
[paper] [bibtex] [book] [press-APNet] [press-IEEE]
Zhi Zhou, Xu Chen, En Li, Liekang Zeng, Ke Luo, Junshan Zhang.
Proceedings of the IEEE (PIEEE), 2019. CCF-A.
🔥 ESI Highly Cited Paper (1500+ Citations).
Selected Awards
- Excellent Reviewer for IEEE Transactions on Network Science and Engineering, 2024
- SYSU Outstanding Ph.D. Graduate (Summa Cum Laude), 2023
- SYSU Presidential Fellowship, 2022
- National Ph.D. Scholarship, 2022
- Professor Shu-Jun Wang Memorial Fellowship, 2021
- Excellent Ph.D. Student Scholarship, 2018-2023
- SYSU Outstanding Undergraduate (Summa Cum Laude), 2018
- Finalist Award, Mathematical Contest in Modeling/Interdisciplinary Contest in Modeling, 2016
- Excellent Undergraduate Student Scholarship, 2014-2018
Working Experience
- Research assistant at National Supercomputing Center in Guangzhou (Feb. 2018 - July 2018)
- Research intern at Cloud & Mobile Research Group, Microsoft Research Asia (Sep. 2017 - Jan. 2018)
Teaching Experience
- DCS6270: Edge Computing. (Spring 2022)
- DCS207: Principles of Computer Organization. (Fall 2021)
- EIT116/EIT118: Digital Circuits and Logical Design. (Spring 2020, Spring 2019)
- DCS110/DCS112: Object-Oriented Programming. (Spring 2019, Spring 2017)
Academic Services
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Program Committee Member
- International Conference on Mobility, Sensing and Networking 2023
- International Workshop on Intelligent Cloud Computing and Networking 2022, 2021 (Co-located with INFOCOM 2022, 2021)
- International Workshop on Mobility in the Evolving Internet Architecture 2019 (Co-located with ICNP 2019)
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Journal Reviewer
- IEEE/ACM Transactions on Networking
- IEEE Journal of Selected Areas in Communications
- IEEE Transactions on Mobile Computing
- IEEE Transactions on Parallel and Distributed Systems
- IEEE Transactions on Wireless Communications
- IEEE Transactions on Network Science and Engineering
- IEEE Transactions on Computers
- IEEE Internet of Things Journal
- IEEE Transactions on Vehicular Technology
Talks
- Fograph: Enabling Real-Time Deep Graph Inference with Fog Computing
Bay Area Ph.D. Symposium, Guangzhou, Dec. 2022
Huawei, Shenzhen, Oct. 2022
WWW, Lyon (Online), Apr. 2022 - AdaDrone: Quality of Navigation Based Neural Adaptive Scheduling for Edge-Assisted Drones
IMT-2030 (6G) Workshop, Apr. 2023
ICDCS, Bologna (Online), July 2022 - CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices
National Supercomputing Center, Guangzhou, Jan. 2022
National Engineering Research Laboratory of Digital Homes, Guangzhou, Nov. 2021
SYSU Edge Computing Seminar, Guangzhou, Apr. 2021 - Edge intelligence: Definition, Taxonomy and Open Challenges
Huawei, Songshan Lake, July 2021