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/cloud computing.
Research Overview:
- Collaborative Edge Intelligence
- 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+ [TMC'24], ChainDP [IWQoS'23]
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Selected Publications
Full Publications, * indicates equal contribution, # indicates corresponding author, + indicates the student mentored by me.
- Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence.
[paper]
[bibtex]
Liekang Zeng, Shengyuan Ye+, Xu Chen, Xiaoxi Zhang, Ju Ren, Jian Tang, Yang Yang, Xuemin (Sherman) Shen.
IEEE Communications Survey and Tutorial, 2025. SCI-1.
- Grape: Efficient Spatiotemporal Prediction Services with Stale Sensing Streams.
[paper]
[bibtex]
Liekang Zeng, Yunchao Liu, Shengyuan Ye, Mu Yuan, Di Duan, Xu Chen, Guoliang Xing.
IEEE Real-Time Systems Symposium, 2025. CCF-A.
- SCX: Stateless KV-Cache Encoding for Cloud-Scale Confidential Transformer Serving.
[paper]
[bibtex]
Mu Yuan, Lan Zhang, Liekang Zeng, Siyang Jiang, Bufang Yang, Di Duan, Guoliang Xing
Annual conference of the ACM Special Interest Group on Data Communication (SIGCOMM), 2025. CCF-A.
- Multi-tier Multi-node Scheduling of LLM for Collaborative AI Computing.
[paper]
[bibtex]
Mulei Ma+, Chenyu Gong+, Liekang Zeng#, Yang Yang.
IEEE International Conference on Computer Communications (INFOCOM), 2025. CCF-A.
- 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.
- Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices.
[paper]
[bibtex]
[slides]
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 (900+ 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 (2000+ Citations).
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