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I am a Lecturer (i.e., Assistant Professor) at the Â鶹ÊÓƵ, United Kingdom. Previously, I received my Bachelor's degree in Electrical Engineering from China Agricultural University in June 2017, my Master's degree in Electrical Engineering from Tianjin University in June 2020, and my Ph.D. degree in Electrical Engineering from Aalborg University in June 2023. From Sept. 2022 to Feb. 2023, I was an exchange student researcher at the Energy Digitalization Laboratory, The University of Hong Kong. From Aug. 2023 to Mar. 2025, I was a postdoctoral researcher at the Wind Engineering and Renewable Energy Laboratory, École Polytechnique Fédérale de Lausanne (EPFL). I am the MSCA Fellow, JSPS Fellow, and DAAD AInet Fellow. Currently, I mainly focus on artificial intelligence in power systems, such as explainable artificial intelligence (XAI) and transfer learning in wind power forecasting, electricity theft detection, and reactive power optimization of power distribution systems. More detail:

Publication List

J1W. Liao, R. Zhu, T. Ishizaki, Y. Li, Y. Jia, and Z. Yang, " Can Gas Consumption Data Improve the Performance of Electricity Theft Detection?," IEEE Transactions on Industrial Informatics, vol. 20, no. 6, pp. 8453-8465, Jun. 2024.

J2 W. Liao, A. Takiddin, M. Tariq, S. Chen, L. Ge and Z. Yang, "Sample Adaptive Transfer for Electricity Theft Detection With Distribution Shifts," IEEE Transactions on Power Systems, vol. 39, no. 6, pp. 7012-7024, Nov. 2024.

J3 W. Liao, Y. Zhang, D. Cao, T. Ishizaki, Z. Yang and D. Yang, "Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model," IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-4, Jan. 2024.

J4 W. Liao, R. Zhu, Z. Yang, K. Liu, B. Zhang ,S. Zhu, and B. Feng, "Electricity Theft Detection Using Dynamic Graph Construction and Graph Attention Network," IEEE Transactions on Industrial Informatics, vol. 20, no. 4, pp. 5074-5086, Apr. 2024.

J5 W. Liao, B. Bak-Jensen, J. R. Pillai, X. Xia, G. Ruan and Z. Yang, "Reducing Annotation Efforts in Electricity Theft Detection Through Optimal Sample Selection," IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-11, Jan. 2024

J6 W. Liao, Z. Yang, K. Liu, B. Zhang, X. Chen and R. Song, "Electricity Theft Detection Using Euclidean and Graph Convolutional Neural Networks," IEEE Transactions on Power Systems, vol. 38, no. 4, pp. 3514-3527, Aug. 2022.

J7 W. Liao, Z. Yang, B. Bak-Jensen, J. Pillai, L. Krannichfeldt, Y. Wang, D. Yang,"Simple Data Augmentation Tricks for Boosting Performance on Electricity Theft Detection Tasks", IEEE Transactions on Industry Applications, vol. 59, no. 4, pp. 4846-4858, Mar. 2023.


J8W. Liao, R. Zhu, A. Takiddin, M. Tariq, G. Ruan, X. Cui,and Z. Yang,"Transfer Learning-Driven Electricity Theft Detection in Small Sample Cases", IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-13, Oct. 2024.

J9 W. Liao, R. Zhu, L. Ge, D. Cao, and Z. Yang," Mitigating Class Imbalance Issues in Electricity Theft Detection via a Sample-Weighted Loss” IEEE Transactions on Industrial Informatics, Accepted( in press), Oct. 2024, doi: 10.1109/TII.2024.3485813.

J10 W. Liao, Z. Yang, X. Chen, and Y. Li, "WindGMMN: Scenario Forecasting for Wind Power Using Generative Moment Matching Networks," IEEE Transactions on Artificial Intelligence, vol. 3, no. 5, pp. 843-850, Nov. 2021.

J11 W. Liao, J. Fang, L. Ye, B. Bak-Jensen, Z. Yang, and F. Porte-Agel, "Can We Trust Explainable Artificial Intelligence in Wind Power Forecasting?," Applied Energy, vol. 376, Dec. 2024.

J12 W. Liao, S. Wang, D. Yang, Z. Yang, J. Fang, C. Rehtanz, and F. Porté-Agel, " TimeGPT in Load Forecasting: A Large Time Series Model Perspective," Applied Energy, Accepted (in press), Dec. 2024.

J13 W. Liao, B. Bak-Jensen, J. R. Pillai, Z. Yang, and K. Liu, "Short-Term Power Prediction for Renewable Energy Using Hybrid Graph Convolutional Network and Long Short-Term Memory Approach," Electric Power Systems Research, vol. 211, pp. 1-7, Oct. 2022.

J14 W. Liao, S. Wang, B. Bak-Jensen, J. R. Pillai, Z. Yang, and K. Liu, "Ultra-short-term Interval Prediction of Wind Power Based on Graph Neural Network and Improved Bootstrap Technique," Journal of Modern Power Systems and Clean Energy, vol. 11, no. 4, pp. 1100-1114, Jan. 2023 (Best Paper Award).

J15 W. Liao, B. Bak-Jensen, J. R. Pillai, Y. Wang, and Y. Wang, "A Review of Graph Neural Networks and Their Applications in Power Systems," Journal of Modern Power Systems and Clean Energy, vol. 10, no. 2, pp. 345-360, Aug. 2021 (ESI Highly Cited Paper; Best Paper Award).

I warmly welcome PhD proposals on topics falling within my research areas.

1. Artificial intelligence in power systems.

2. Wind and solar power forecasting, load forecasting

3.Power system optimization

4. Electricity theft detection, classification in power systems

For applicants requiring a scholarship, such as CSC, to fund their studies, I would be happy to support the application.

I'm responsible for joint education programmes with the China Three Gorges University for 2nd and 1st year undergraduates.

Main modules are:

Circuits and systems I

Circuits and systems II

Electronics I

Electronics II

Prog and numerical methods