Dr Dongzhu Liu

  • Lecturer in Cybersecurity (School of Computing Science)

email: Dongzhu.Liu@glasgow.ac.uk

SAWB 510(b) Sir Alwyn Williams Building, University of Glasgow, Glasgow City, Scotland, United Kingdom, G12 8RZ

Import to contacts

ORCID iDhttps://orcid.org/0000-0001-7820-9531

Biography

I am a lecturer at System Section (GLASS), School of Computing Science, University of Glasgow. I received the PhD degree from the University of Hong Kong, under the supervision of Prof. Kaibin Huang in 2019, and the B.Eng. degree from the University of Electronic Science and Technology of China (UESTC) in 2015. Prior to joining University of Glasgow, I was a postdoctoral research associate at the Department of Engineering, King's College London, working with Prof. Osvaldo Simeone.

 

Research interests

  • Communication-Efficient Federated Learning
  • Differential Privacy
  • Bayesian Learning 
  • Distributed Multimodal Learning 
  • Edge AI  
  • Wireless Networks 
  • Signal Processing 

[Google Scholar] 

[Personal Website]

Publications

List by: Type | Date

Jump to: 2025 | 2024 | 2023 | 2022 | 2021 | 2020 | 2018
Number of items: 13.

2025

Zhang, B., Liu, D. , Simeone, O., Wang, G., Pezaros, D. and Zhu, G. (2025) Personalizing Low-rank Bayesian Neural Networks Via Federated Learning. Artificial Intelligence and Statistics (AISTATS 2025), Mai Khao, Thailand, 3-5 May 2025. (Accepted for Publication)

Yang, M., Liang, G. , Liu, D. , Zhang, L. and Huang, K. (2025) Channel Capacity-Aware Distributed Encoding for Multi-View Sensing and Edge Inference. In: IEEE International Conference on Communications (ICC), Montreal, Canada, 8–12 June 2025, (Accepted for Publication)

2024

Guo, M., Liu, D. , Simeone, O. and Wen, D. (2024) Efficient wireless federated learning via low-rank gradient factorization. IEEE Transactions on Vehicular Technology, (doi: 10.1109/TVT.2024.3506950) (Early Online Publication)

Zhang, B., Liu, D. , Simeone, O. and Zhu, G. (2024) Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics. In: IEEE Global Communications Conference (GLOBECOM 2023), Kuala Lumpur, Malaysia, 4–8 Dec 2023, pp. 5286-5291. ISBN 9798350310900 (doi: 10.1109/GLOBECOM54140.2023.10437650)

2023

Zhang, M., Li, Y., Liu, D. , Jin, R., Zhu, G., Zhong, C. and Quek, T. Q.S. (2023) Joint compression and deadline optimization for wireless federated learning. IEEE Transactions on Mobile Computing, (doi: 10.1109/tmc.2023.3344108) (Early Online Publication)

Xing, H., Zhu, G., Liu, D. , Wen, H., Huang, K. and Wu, K. (2023) Task-oriented integrated sensing, computation and communication for wireless edge AI. IEEE Network, 37(4), pp. 135-144. (doi: 10.1109/MNET.011.2300046)

Liu, D. and Simeone, O. (2023) Wireless federated Langevin Monte Carlo: repurposing channel noise for Bayesian sampling and privacy. IEEE Transactions on Wireless Communications, 22(5), pp. 2946-2961. (doi: 10.1109/TWC.2022.3215663)

2022

Liu, D. and Simeone, O. (2022) Channel-driven Monte Carlo sampling for Bayesian distributed learning in wireless data centers. IEEE Journal on Selected Areas in Communications, 40(2), pp. 562-577. (doi: 10.1109/JSAC.2021.3118406)

2021

Liu, D. , Zhu, G., Zhang, J. and Huang, K. (2021) Data-importance aware user scheduling for communication-efficient edge machine learning. IEEE Transactions on Cognitive Communications and Networking, 7(1), pp. 265-278. (doi: 10.1109/TCCN.2020.2999606)

Liu, D. and Simeone, O. (2021) Privacy for free: wireless federated learning via uncoded transmission with adaptive power control. IEEE Journal on Selected Areas in Communications, 39(1), pp. 170-185. (doi: 10.1109/JSAC.2020.3036948)

Liu, D. , Zhu, G., Zeng, Q., Zhang, J. and Huang, K. (2021) Wireless data acquisition for edge learning: data-importance aware retransmission. IEEE Transactions on Wireless Communications, 20(1), pp. 406-420. (doi: 10.1109/TWC.2020.3024980)

2020

Zhu, G., Liu, D. , Du, Y., You, C., Zhang, J. and Huang, K. (2020) Toward an intelligent edge: wireless communication meets machine learning. IEEE Communications Magazine, 58(1), pp. 19-25. (doi: 10.1109/MCOM.001.1900103)

2018

Liu, D. and Huang, K. (2018) Mitigating interference in content delivery networks by spatial signal alignment: the approach of shot-noise ratio. IEEE Transactions on Wireless Communications, 17(4), pp. 2305-2318. (doi: 10.1109/TWC.2018.2791523)

This list was generated on Thu May 15 23:35:12 2025 BST.
Jump to: Articles | Conference or Workshop Item | Conference Proceedings
Number of items: 13.

Articles

Guo, M., Liu, D. , Simeone, O. and Wen, D. (2024) Efficient wireless federated learning via low-rank gradient factorization. IEEE Transactions on Vehicular Technology, (doi: 10.1109/TVT.2024.3506950) (Early Online Publication)

Zhang, M., Li, Y., Liu, D. , Jin, R., Zhu, G., Zhong, C. and Quek, T. Q.S. (2023) Joint compression and deadline optimization for wireless federated learning. IEEE Transactions on Mobile Computing, (doi: 10.1109/tmc.2023.3344108) (Early Online Publication)

Xing, H., Zhu, G., Liu, D. , Wen, H., Huang, K. and Wu, K. (2023) Task-oriented integrated sensing, computation and communication for wireless edge AI. IEEE Network, 37(4), pp. 135-144. (doi: 10.1109/MNET.011.2300046)

Liu, D. and Simeone, O. (2023) Wireless federated Langevin Monte Carlo: repurposing channel noise for Bayesian sampling and privacy. IEEE Transactions on Wireless Communications, 22(5), pp. 2946-2961. (doi: 10.1109/TWC.2022.3215663)

Liu, D. and Simeone, O. (2022) Channel-driven Monte Carlo sampling for Bayesian distributed learning in wireless data centers. IEEE Journal on Selected Areas in Communications, 40(2), pp. 562-577. (doi: 10.1109/JSAC.2021.3118406)

Liu, D. , Zhu, G., Zhang, J. and Huang, K. (2021) Data-importance aware user scheduling for communication-efficient edge machine learning. IEEE Transactions on Cognitive Communications and Networking, 7(1), pp. 265-278. (doi: 10.1109/TCCN.2020.2999606)

Liu, D. and Simeone, O. (2021) Privacy for free: wireless federated learning via uncoded transmission with adaptive power control. IEEE Journal on Selected Areas in Communications, 39(1), pp. 170-185. (doi: 10.1109/JSAC.2020.3036948)

Liu, D. , Zhu, G., Zeng, Q., Zhang, J. and Huang, K. (2021) Wireless data acquisition for edge learning: data-importance aware retransmission. IEEE Transactions on Wireless Communications, 20(1), pp. 406-420. (doi: 10.1109/TWC.2020.3024980)

Zhu, G., Liu, D. , Du, Y., You, C., Zhang, J. and Huang, K. (2020) Toward an intelligent edge: wireless communication meets machine learning. IEEE Communications Magazine, 58(1), pp. 19-25. (doi: 10.1109/MCOM.001.1900103)

Liu, D. and Huang, K. (2018) Mitigating interference in content delivery networks by spatial signal alignment: the approach of shot-noise ratio. IEEE Transactions on Wireless Communications, 17(4), pp. 2305-2318. (doi: 10.1109/TWC.2018.2791523)

Conference or Workshop Item

Zhang, B., Liu, D. , Simeone, O., Wang, G., Pezaros, D. and Zhu, G. (2025) Personalizing Low-rank Bayesian Neural Networks Via Federated Learning. Artificial Intelligence and Statistics (AISTATS 2025), Mai Khao, Thailand, 3-5 May 2025. (Accepted for Publication)

Conference Proceedings

Yang, M., Liang, G. , Liu, D. , Zhang, L. and Huang, K. (2025) Channel Capacity-Aware Distributed Encoding for Multi-View Sensing and Edge Inference. In: IEEE International Conference on Communications (ICC), Montreal, Canada, 8–12 June 2025, (Accepted for Publication)

Zhang, B., Liu, D. , Simeone, O. and Zhu, G. (2024) Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics. In: IEEE Global Communications Conference (GLOBECOM 2023), Kuala Lumpur, Malaysia, 4–8 Dec 2023, pp. 5286-5291. ISBN 9798350310900 (doi: 10.1109/GLOBECOM54140.2023.10437650)

This list was generated on Thu May 15 23:35:12 2025 BST.

Supervision

  • Liang, Guangming
    Generative Artificial Intelligence for Wireless Digital Twin Networks: Algorithm Design and Performance Analysis
  • Yang, Mingjie
    Privacy-Aware Digital Communication for Robust Federated Learning: Algorithm Design and Performance Analysis
  • ZHANG, Boning
    Federated Learning for Heterogeneous Models with Knowledge Transfer: Algorithm Design and Performance Analysis

Teaching

  • COMPSCI 4062/5063 Cyber Security Fundamentals, Spring 2022, 2023.
  • COMPSCI 4046 Professional Software Development H and Team Projects 2022-2023. 
  • COMPSCI 5110 Emerging Topics in Cyber Security, Spring 2022.

Additional information

Services

Technical Program Committee

  • IEEE Globecom 2022, 2021
  • IEEE ICC 2023, 2021
  • IEEE PIMRC 2021

Technical Review

  • IEEE Journal on Selected Areas in Communications (JSAC)
  • IEEE Wireless Communications Magazine
  • IEEE Transactions on Wireless Communications (TWC)
  • IEEE Transactions on Communications (TCom)
  • IEEE Transactions on Green Communications and Networking (TGCN)
  • IEEE Communications Letters (CL)
  • IEEE Wireless Communications Letters (WCL)
  • IEEE International Symposium on Information Theory (ISIT)
  • IEEE International Conference on Communications (ICC)
  • IEEE Global Communications Conference (Globecom)
  • IEEE International Workshop on Signal Processing Advances in Wireless Comm. (SPAWC)
  • IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
  • IEEE Information Theory Workshop (ITW)