About Me

Dr Wanchun Liu is a Senior Lecturer and an ARC Discovery Early Career Researcher Award (DECRA) Fellow at the Faculty of Engineering, the University of Sydney.

Her main research area is wireless networked control for the Industrial Internet of Things and Cyber-Physical Systems. Currently, she focuses on advancing theoretical research in wireless networked control and undertaking practical projects in networked robotics (see demos here, here, and here). Through developing cutting-edge theories and algorithms that unify control, communication, and computing, her work addresses key challenges in this domain. Recently, she has also begun pioneering research in the emerging area of wireless human-machine collaboration (see paper here), aiming to push the boundaries of this innovative field.

She has also pioneered the foundational groundwork 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.

Recent Papers on machine learning-based communications and control:

• J. Chen and W. Liu, "Goal-oriented Transmission Scheduling: Structure-guided DRL with a Unified Dual On-policy and Off-policy Approach", submitted, 2025 (arXiv)

• G. Pang, W. Liu, et al., "Communication-Control Codesign for Large-Scale Wireless Networked Control Systems," IEEE Journal on Selected Areas in Communications, 2025 (arXiv)

• G. Pang, K. Huang, D. E. Quevedo, B. Vucetic, Y. Li, W. Liu "Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control", in IEEE Transactions on Cybernetics, 2025 (arXiv)

• K. Wang, W. Liu, et al., "Wireless Resource Allocation with Collaborative Distributed and Centralized DRL under Control Channel Attacks", submitted, 2024 (arXiv)

• J. Chen, W. Liu, et al., "Semantic-aware Transmission Scheduling: a Monotonicity-driven Deep Reinforcement Learning Approach", in IEEE Communications Letters 2024 (arXiv)

• J. Chen, W. Liu, et al., "Structure-Enhanced DRL for Optimal Transmission Scheduling", in IEEE Transactions on Wireless Communications, 2023 (arXiv)

• Z. Zhao, W. Liu, et al., "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, et al., "DRL-based Resource Allocation in Remote State Estimation", in IEEE Transactions on Wireless Communications (arXiv)

Email: wanchun.liu AT sydney.edu.au

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