Selected Journal/Magazine Papers complete list in Google Scholar

  1. B. Zhu, Y. Zhu, C. Chen, L. Kong. “Trident: A Provider-Oriented Resource Management Framework for Serverless Computing Platforms“, to appear in IEEE Transactions on Services Computing, 2025 (CCF-A)
  2. Z. Wang, H. Ji, Y. Zhu, D. Wang, Z. Han. “A Survey on Federated Analytics: Taxonomy, Enabling Techniques, Applications and Open Issues“,  in IEEE Communications Surveys and Tutorials, 2025
  3. S. Cen, Y. Zhu. “NP-LLM: A Unified Large-language-model-assisted Framework of 6G Network-layer Planning“,  in IEEE Communications Magazine, 2025
  4. Z. Li, Y. Zhu, S. Mumtaz, L. Kong, B. Li. “RIVA: Communication-Efficient Streaming Control for Real-time Industrial Video Analytics“,  in IEEE Journal on Selected Areas in Communications (JSAC),  2025 (CCF-A)
  5. X. Yuan, M. Wu, Z. Wang, Y. Zhu, M. Ma, J. Guo, Z. Zhang, W. Zhu. “Understanding 5G Performance for Real-world Services: a Content Provider’s Perspective“,  in IEEE/ACM Transactions on Networking, 2025 (CCF-A)
  6. Y. Kang, Y. Zhu, D. Wang, Z. Han, “Efficient Path Selection Design for Large Scale LEO Satellite Constellations Using Graph Embedding-Based Reinforcement Learning“, in IEEE Transactions on Network Science and Engineering, 2025
  7. S. Xie, Y. Xue, Y. Zhu, Z. Wang, “SkyML: A MLaaS Federation Design for Multicloud-based Multimedia Analytics“, in IEEE Transactions on Multimedia, 2024
  8. Z. Wang, Y. Zhu, D. Wang, Z. Han, “Towards Fair and Scalable Trial Assignment in Federated Bandits: A Shapley Value Approach“, in IEEE Transactions on Big Data, 2024
  9. S. Cen, M. Zhang, Y. Zhu, J. Liu, “AdaDSR: Adaptive Configuration Optimization for Neural Enhanced Video Analytics Streaming“, in IEEE Internet of Things Journal, 2023
  10. Y. Kang, Y. Zhu, D. Wang, Z. Han, T. Basar, “Joint Server Selection and Handover Design for Satellite-Based Federated Learning Using Mean-field Evolutionary Approach”,  in IEEE Transactions on Network Science and Engineering, 2023.
  11. Q. Pan, H. Cao, Y. Zhu, J. Liu, B. Li, “Contextual Client Selection for Efficient Federated Learning over Edge Devices“, in IEEE Transactions on Mobile Computing, 2023. (CCF-A)
  12. S. Shi, Y. Guo, D. Wang, Y. Zhu, Z. Han, “Distributionally Robust Federated Learning for Network Traffic Classification with Noisy Labels“, in IEEE Transactions on Mobile Computing, 2023. (CCF-A)
  13. W. Gong, L. Cao, Y. Zhu, F. Zuo, X. He, H. Zhou, “Federated Inverse Reinforcement Learning for Smart ICUs with Differential Privacy“, in IEEE Internet of Things Journal, 2023
  14. C. Wu, Y. Zhu, R. Zhang, Y. Chen, F. Wang, S. Cui, “FedAB: Truthful Federated Learning with Auction-based Combinatorial Multi-Armed Bandit“, in IEEE Internet of Things Journal, 2023
  15. B. Zhu, S. Lin, Y. Zhu, X. Wang, “Collaborative Hyperspectral Image Processing using Satellite Edge Computing“, in IEEE Transactions on Mobile Computing, 2023. (CCF-A)
  16. S. Shi, C. Hu, D. Wang, Y. Zhu, Z. Han, “Federated HD Map Updating through Overlapping Coalition Formation Game“, in IEEE Transactions on Mobile Computing, 2023. (CCF-A)
  17. D. Chen, Y. Zhu, D. Wang, H. Wang, J. Xie, X. Zhang, Z. Han, “Love of Variety based Latency Analysis for High Definition Map Updating: Age of Information and Distributional Robust Perspectives“, in IEEE Transactions on Intelligent Vehicles, 2022
  18. Z. Wang, Y. Zhu, D. Wang, Z. Han, “Secure Trajectory Publication in Untrusted Environments: A Federated Analytics Approach“, in IEEE Transactions on Mobile Computing, 2022. [Code] (CCF-A)
  19. Z. Wang, Y. Zhu, D. Wang, Z. Han, “Federated Analytics Informed Distributed Industrial IoT Learning with Non-IID Data“, in IEEE Transactions on Network Science and Engineering, 2022. [Code]
  20. T. Wang, S. Chen, Y. Zhu, A. Tang, and X. Wang, “LinkSlice: Fine-grained Network Slice Enforcement Based on Deep Reinforcement Learning“, in IEEE Journal on Selected Areas in Communications, 2022. (CCF-A)
  21. M. Zhang, Y. Zhu, J. Liu, F. Wang, F. Wang, “CharmSeeker: Automated Pipeline Configuration for Serverless Video Processing“, in IEEE/ACM Transactions on Networking, 2022. (CCF-A)
  22. J. Zhang, S. Chen, X. Wang, Y. Zhu, “Dynamic Reservation of Edge Servers via Deep Reinforcement Learning for Connected Vehicles“, in IEEE Transactions on Mobile Computing, 2021. (CCF-A)
  23. D. Wang, S. Shi, Y. Zhu, Z. Han. “Federated Analytics: Opportunities and Challenges“,  in IEEE Network, 2021.
  24. M. Zhang, F. Wang, Y. Zhu, J. Liu, B. Li. “Serverless Empowered Video Analytics for Ubiquitous Networked Cameras“,  in IEEE Network, 2021.
  25. S. Shi, C. Hu, D. Wang, Y. Zhu, Z. Han, “Federated Anomaly Analytics for Local Model Poisoning Attack“, in IEEE Journal on Selected Areas in Communications, 2021. (CCF-A)
  26. D. Chen, D. Wang, Z. Han, Y. Zhu, “Digital Twin for Federated Analytics Using A Bayesian Approach“, in IEEE Internet of Things Journal, 2021
  27. F. Wang, C. Zhang, F. Wang, J. Liu, Y. Zhu, H. Pang, L. Sun, “DeepCast: Towards Personalized QoE for Edge-Assisted Crowdcast With Deep Reinforcement Learning“, in IEEE/ACM Transactions on Networking, 2020 (CCF-A)
  28. F. Wang, Y. Zhu, F. Wang, J. Liu, X. Ma, X. Fan.  “Car4Pac: Last Mile Parcel Delivery through Intelligent Car Trip Sharing“, in IEEE Transactions on Intelligent Transportation Systems, 2019.
  29. Y. Zhu, Q. He, J. Liu, B. Li, Y. Hu. “When Crowd Meets Big Video Data: Cloud-Edge Collaborative Transcoding for Personal Livecast“, in IEEE Transactions on Network Science and Engineering, 2018.
  30. Y. Zhu, S. Fu, J. Liu, Y. Cui. “Truthful Online Auction Towards Maximized Instance Utilization in the Cloud“, in IEEE/ACM Transactions on Networking, 2018. (CCF-A)

Selected Conference Papers

  1. Z. Jiang, X. Feng, T. Huang, R. Zhang, P. Weng, Y. Zhu, “Progressive Learning with Human Feedback for Personalized Adaptive Video Streaming“, to appear in ACM Multimedia 2025 (CCF-A)
  2. H. Zhao, Y. Zhu, “SkyLLM: Cross-LLM-APIs Federation for Cost-effective Query Processing“, in ACL findings, 2025
  3. Z. Yang, S. Cen, Y. Zhu, “How Resilient Are They? Robustness Analysis of LEO Satellite Routing“, in IEEE/ACM IWQoS 2025 [code]
  4. B. Zhu, C. Chen, X. Fan, Y. Zhu, “LLMSched: Uncertainty-Aware Workload Scheduling for Compound LLM Applications“, to appear in IEEE ICDCS 2025
  5. Z. Wang, Y. Zhu, “NeRFlex: Resource-aware Real-time High-quality Rendering of Complex Scenes on Mobile Devices“, to appear in IEEE ICDCS 2025
  6. Z. Jiang, X. Feng, P. Weng, Y. Zhu, Y. Song, T. Zhou, Y. Hu, T. Lv, C. Fan, “Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards“,  in ICLR 2025
  7. X. Feng, Z. Jiang, T. Kaufmann, E. Hüllermeier, P. Weng, Y. Zhu, “Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries”,  in ICML 2025 (CCF-A)
  8. X. Feng, Z. Jiang, T. Kaufmann, P. Xu, E. Hullermeier, P. Weng, Y. Zhu, “DUO: Diverse, Uncertain, On-Policy Query Generation and Selection for Reinforcement Learning from Human Feedback“,  in AAAI 2025 (CCF-A)
  9. Y. Zhao, W.Wang, X. Wang, L. Kong, J. Yu, Y. Zhu, S. Li, C. He, G. Chen. “B2LoRa: Boosting LoRa Transmission for Satellite-IoT Systems with Blind Coherent Combining“, in ACM MOBICOM, 2025 (CCF-A)
  10. R. Lu, Y. Jiang, J. Zhang, C. Li, Y. Zhu, B. Chen, Z. Wang, “gamma-FedHT: Stepsize-Aware Hard-Threshold Gradient Compression in Federated Learning“,  in IEEE INFOCOM 2025 (CCF-A)
  11. L. Jiang, S. Fu, Y. Zhu, B. Li, “Janus: Collaborative Vision Transformer Under Dynamic Network Environment“,  in IEEE INFOCOM 2025 (CCF-A)
  12. S. Cen, Q. Pan, Y. Zhu, B. Li, “SatFlow: Scalable Network Planning for LEO Mega-Constellations“, in IEEE ICNP 2024
  13. H. Zhao, S. Cen, Y. Zhu, “The Space above the Sky: Uniting Global-Scale Ground Station as a Service for Efficient Orbital Data Processing“,  in IEEE ICNP 2024
  14. Z. Wang, Y. Zhu, “Towards Real-Time Neural Volumetric Rendering on Mobile Devices: A Measurement Study“, in ACM SIGCOMM Workshop on Emerging Multimedia Systems 2024
  15. Z. Li, M. Zhang, Y. Zhu, “OAVS: Efficient Online Learning of Streaming Policies for Drone-sourced Live Video Analytics“, in IEEE/ACM IWQoS 2024
  16. Y. Liu, Z. Wang, Y. Zhu, C. Chen, “DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service“, in IEEE INFOCOM 2024 (CCF-A)
  17. Z. Wang, Y. Zhu, D. Wang, Z. Han, “Federated Analytics-Empowered Frequent Pattern Mining for Decentralized Web 3.0 Applications“, in IEEE INFOCOM 2024 (CCF-A)
  18. J. Huang, Y. Zhu, “SpaceMeta: Global-Scale Massive Multi-User Virtual Interaction over LEO Satellite Constellations“,  in IEEE Satellite 2023
  19. M. Zhang, J. Li, J. Shi, Y. Zhu, L. Zhang, H. Wang, “ITSVA: Toward 6G-Enabled Vision Analytics over Integrated Terrestrial-Satellite Network“, in IEEE Satellite 2023
  20. D. Song, C. Zhang, Y. Zhu, J. Liu, “LiGo: A Low Cost Cross-Platform Deployment Framework Empowers Video Processing Application“, in ACM NOSSDAV 2023
  21. Q. Pan, Y. Zhu, L. Chu, “Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices“, in IEEE ICDE 2023 (CCF-A)
  22. M. Zhang, Y. Zhu, L. Shen, F. Wang, J. Liu, “OmniSense: Towards Edge-Assisted Online Analytics for 360-Degree Videos“, in IEEE INFOCOM 2023 (CCF-A)
  23. S. Fu, D. Reimer, S. Dong, Y. Zhu, S. Ratnasamy, “Comverse: A Federative-by-Design Platform for Community Computing“, CoRR abs/2308.15219, 2023
  24. C. Wu, Y. Zhu, F. Wang, “DSFL: Decentralized Satellite Federated Learning for Energy-Aware LEO Constellation Computing“, in IEEE Satellite 2022  (Best Student Paper Award)
  25. Y. Zhu, W. Bao, D. Wang, J. Liu. “A Stackelberg Queuing Model and Analysis for the Emerging Connection-based Pricing in IoT Markets“,  in IEEE MASS, 2022
  26. K. Chen, Y. Zhu, Z. Han, X. Wang. “Adaptive Cross-Camera Video Analytics at the Edge“, in IEEE MASS, 2022
  27. K. Chen, Y. Zhu, Y. Kang, Z. Han. “Few-Shot Correlation Estimation for Cross-Camera Video Analytics: A Mean-Field Game Approach“, in IEEE PIMRC, Native-AI in wireless networks workshop, 2022
  28. C. Tang, K. Ouyang, Z. Wang, Y. Zhu, W. Ji, Y. Wang, W. Zhu. “Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance“, in ECCV 2022
  29. Y. Lu, Y. Zhu, Z. Wang. “Personalized 360-Degree Video Streaming: A Meta-Learning Approach“, in ACM Multimedia, 2022 (CCF-A)
  30. C. Tang, H. Zhai, K. Ouyang, Z. Wang, Y. Zhu, W. Zhu. “Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference Approach“,  in ACM Multimedia, 2022 (CCF-A)
  31. Q. Pan, Y. Zhu. “FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy“, in ACM SIGKDD, 2022 (CCF-A)
  32. X. Yuan, M. Wu, Z. Wang, Y. Zhu, M. Ma, J. Guo, Z. Zhang, W. Zhu. “Understanding 5G Performance for Real-world Services: a Content Provider’s Perspective“,  in ACM SIGCOMM, 2022 (CCF-A)
  33. S. Shi, C. Hu, D. Wang, Y. Zhu, Z Han. “Distributionally Robust Federated Learning for Differentially Private Data“, in IEEE ICDCS, 2022
  34. H. Cao, Q. Pan, Y. Zhu, J. Liu.”Birds of a Feather Help: Context-aware Client Selection for Federated Learning“,  in International Workshop on Trustable, Verifiable and Auditable Federated Learning in Conjunction with AAAI 2022
  35. Z. Wang, Y. Zhu, D. Wang, Z. Han. “FedFPM: A Unified Federated Analytics Framework for Collaborative Frequent Pattern Mining“, in IEEE INFOCOM, 2022. [Code] (CCF-A)
  36. S. Xie, Y. Xue, Y. Zhu, Z. Wang. “Cost Effective MLaaS Federation: A Combinatorial Reinforcement Learning Approach“,  in IEEE INFOCOM, 2022 (CCF-A)
  37. M. Zhang, F. Wang, Y. Zhu, J. Liu, Z. Wang. “Towards Cloud-Edge Collaborative Online Video Analytics with Fine-Grained Serverless Pipelines“, in ACM MMSys, 2021.
  38. Z. Wang, Y. Zhu, D. Wang, Z. Han. “FedACS: Federated Skewness Analytics in Heterogeneous Decentralized Data Environments“, in IEEE/ACM IWQoS, 2021
  39. J. Zhang, S. Chen, X. Wang, Y. Zhu. “DeepReserve: Dynamic Edge Server Reservation for Connected Vehicles with Deep Reinforcement Learning“, in IEEE INFOCOM, 2021 (CCF-A)
  40. M. Zhang, Y. Zhu, C. Zhang, J. Liu. “Video processing with serverless computing: a measurement study“, in ACM NOSSDAV, 2019
  41. F. Wang, C. Zhang, J. Liu, Y. Zhu, H. Pang, L. Sun. “Intelligent Edge-Assisted Crowdcast with Deep Reinforcement Learning for Personalized QoE“, in IEEE INFOCOM, 2019 (CCF-A)
  42. Y. Huang, Y. Zhu, X. Fan, X. Ma, F. Wang, J. Liu, Z. Wang, Y. Cui. “Task Scheduling with Optimized Transmission Time in Collaborative Cloud-Edge Learning“, in IEEE ICCCN, 2018
  43. F. Wang, Y. Zhu, F. Wang, J. Liu. “Ridesharing as a Service: Exploring Crowdsourced Connected Vehicle Information for Intelligent Package Delivery“, in IEEE/ACM IWQoS, 2018
  44. Y. Zhu, J. Liu, Z. Wang, C. Zhang. “When Cloud Meets Uncertain Crowd: An Auction Approach for Crowdsourced Livecast Transcoding“, in ACM Multimedia, 2017 (CCF-A)
  45. S. Fu, Y. Zhu, J. Liu. “HARV: Harnessing hybrid virtualization to improve instance (re) usage in public cloud“, in IEEE/ACM IWQoS, 2017
  46. Y. Zhu, S. Fu, J. Liu, Y. Cui. “Truthful Online Auction for Cloud Instance Subletting“, in IEEE ICDCS, 2017
  47. Y. Zhu, J. Jiang, B. Li, B. Li. “Rado: A Randomized Auction Approach for Data Offloading via D2D Communication“, in IEEE MASS, 2015
  48. J. Jiang, Y. Zhu, B. Li, B. Li. “Rally: Device-to-device content sharing in LTE networks as a game“, IEEE MASS, 2015

Demos and Posters

  1. Y. Zhu, B. Zhu, C. Chen, X. Fan. “Towards Efficient Compound Large Language Model System Serving in the Wild“, in IEEE/ACM IWQoS 2024 (Best Poster Award)
  2. D. Song, Y. Zhu, C. Zhang, J. Liu. “Trueno: A Cross-Platform Machine Learning Model Serving Framework in Heterogeneous Edge Systems“, in IEEE INFOCOM 2022
  3. Y. Zhu, J. Liu. “C2: Procuring uncertain freelancers for interactive live video transcoding“, in IEEE/ACM IWQoS 2017

Book Chapter

  1. D. Chen, D. Wang, Y. Zhu, and Z. Han, “Digital Twin for Federated Analytics Applications,” Handbook of Digital Twins, CRC Press