About Me

News: PhD scholarships available in advanced wireless networked control and robotics in the 6G era!

Dr Wanchun Liu is an ARC Discovery Early Career Researcher Award (DECRA) Fellow at the School of Electrical and Information Engineering, the University of Sydney.

Her main research area is wireless networked control for Industrial Internet of Things and Cyber-Physical Systems. Currently, she is focusing on theoretical research of wireless networked control and practical projects in networked robotics by developing cutting-edge theories and algorithms for joint control, communication, and computing.

Some robotics-related project demos can be found here and here.

She is also interested in

1) splitting receiver design (paper 1, paper 2, paper 3, paper 4) for the next-generation high-throughput, low-latency, and highly reliable communications, and

2) over-the-air computation (paper 1, paper 2, paper 3, paper 4) for large-scale data fusion of ubiquitous wireless sensors.

Project descriptions can be found here.

Recent Papers on machine-learning-based communications and control:

•  J. Chen, W. Liu, D. E. Quevedo, Y. Li, B. Vucetic, "Semantic-aware Transmission Scheduling: a Monotonicity-driven Deep Reinforcement Learning Approach", in IEEE Communications Letters 2024 (arXiv)

• J. Chen, W. Liu, D. E. Quevedo, S. R. Khosravirad, Y. Li, B. Vucetic, "Structure-Enhanced DRL for Optimal Transmission Scheduling", in IEEE Transactions on Wireless Communications, 2023 (arXiv)

• J. Chen, W. Liu, D. E. Quevedo, Y. Li, B. Vucetic, "Structure-Enhanced Deep Reinforcement Learning for Optimal Transmission Scheduling", in Proc. IEEE ICC 2023 (arXiv)

• Z. Zhao, W. Liu, D. E. Quevedo, Y. Li, B. Vucetic, "Deep Learning for Wireless Networked Systems: a joint Estimation-Control-Scheduling Approach", in IEEE Internet of Things Journal, 2023 (arXiv, GitHub)

• K. Wang, W. Liu, T. Lim, "Deep Learning for Radio Resource Allocation under DoS Attack", in IEEE Transactions on Machine Learning in Communications and Networking, 2024

• A. Leong, D. Quevedo, and W. Liu "Stability Enforced Bandit Algorithms for Channel Selection in Remote State Estimation of Gauss-Markov Processes", in IEEE Transactions on Automatic Control, 2023 (arXiv)

• G. Pang, W. Liu, Y. Li, B. Vucetic, "DRL-based Resource Allocation in Remote State Estimation", in IEEE Transactions on Wireless Communications (arXiv)

• G. Pang, W. Liu, Y. Li, B. Vucetic, "Deep Reinforcement Learning for Radio Resource Allocation in NOMA-based Remote State Estimation", in IEEE Globecom 2022 (arXiv)

• K. Wang, W. Liu and T. Lim "Deep Reinforcement Learning for Joint Sensor Scheduling and Power Allocation under DoS Attack" in ICC 2022, 

• W. Liu, K. Huang, D. E. Quevedo, B. Vucetic and Y. Li, "Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control", submitted, 2021

Recent Events:

• • I am co-organizing a workshop at IEEE 97th Vehicular Technology Conference Spring, "digital twin-enabled industrial wireless control: communications, sensing and computation" (Link). Welcome to join us in Florence, Italy 18-21 June 2023!

  • I am the lead contributor to the IEEE Communications Society Best Reading List on "Communications in Wireless Networked Control" (Link)

  • I am co-organizing the Frontiers Research Topic on "Networked Control Systems for IIoT" (Link). Welcome to submit papers!

Email: wanchun.liu AT sydney.edu.au

Address: J13, The University of Sydney, Darlington, NSW 2008, Australia