I am currently a postdoctoral fellow (Co-Principal Investigator) at the Frontier of Artificial Networks Lab, Department of Data Science, City University of Hong Kong (Supervisor: Prof. Feng-Lei Fan).

I hold a PhD from Harbin Institute of Technology, under the supervision of Prof. SUN Jinwei and Prof. ZHANG Shiping, and a PhD degree at The Hong Kong Polytechnic University, supervised by Prof. ZHANG Xiaoge.

My research interests revolve around signal processing, prognostics & health management (PHM), and model compression. I have published 10+ papers at the flagship journals such as TPAMI, TII, MSSP, TIM, TAI.

Openings

I am seeking self-motivated students for remote positions as Intern Engineers and Research Assistants. Successful applicants will be affiliated with the Shenzhen Research Institute of Big Data (深圳市大数据研究院), a research institute of the Chinese University of Hong Kong (Shenzhen). Our research focuses on LLM foundation models, AI agents, industrial AI, and PHM. If you are interested in these areas, please feel free to contact me at jingxiao.liao[at]cityu.edu.hk.

Our research group can provide internship certificates and recommendation letters for outstanding students, and support applications for Ph.D. programs in the United States and Hong Kong SAR.

🔥 News

• 2026.03 Our paper “A Wearable Multimodal Measurement System With Self-Developed IMU and Plantar Pressure Sensors for Real-Time Gait Recognition” has been accepted at Micromachines.

• 2026.03 We have three papers recognized as ESI highly cited paper in this year.

• 2026.02 Our paper “A Class-Aware Supervised Contrastive Quadratic Neural Network for Imbalanced Bearing Fault Diagnosis” has been accepted at IEEE Transactions on Reliability.

• 2026.01 Our paper “Prior knowledge-embedded first-layer interpretable paradigm for rail transit vehicle human-computer collaboration fault monitoring” has been accepted at Journal of Industrial Information Integration.

• 2025.12 I have successfully defended my PhD dissertation in PolyU and became a dual Ph.D.

• 2025.11 Our paper “Chaos-inspired active learning for physics-informed neural networks to assess the reliability of multi-state systems” has been accepted at Reliability Engineering & System Safety.

• 2025.08 Our paper “Marginal Contribution Spectral Fusion Network for Remote Hyperspectral Soil Organic Matter Estimation” has been accepted at Remote Sensing.

• 2025.08 I have successfully defended my PhD dissertation and became a Ph.D.

• 2025.07 Our paper “One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networks” has been accepted at IEEE Transactions on Pattern Analysis and Machine Intelligence.

• 2025.03 Our tutorial proposal “Recently Advancement of Introducing Neural Diversity into Deep Learning “ has been accepted for presentation at the 2025 International Joint Conference on Neural Networks (IJCNN) Slide.

📝 Publications

Representative Works

• IEEE TPAMI FL Fan, HC Dong, Z Wu, L Ruan, T Zeng, Y Cui, JX Liao*, One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networks
• MSSP JX Liao, C He, J Li, J Sun, S Zhang, X Zhang, Classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise, Mechanical Systems and Signal Processing, (ESI High Cited Paper)
• IEEE TII JX Liao , J Li, HC Dong, M Zhang, S Zhang, X Zhang* Logarithmic Cumulative Transformation: A Simple Yet Effective Approach for Bearing Remaining Useful Life Prediction
• IEEE TIM JX Liao, HC Dong, ZQ Sun, J Sun, S Zhang, FL Fan, Attention-embedded Quadratic Network (Qttention) for Effective and Interpretable Bearing Fault Diagnosis, (ESI High Cited Paper)
• IEEE TAI JX Liao, BJ Hou, HC Dong, H Zhang, X Zhang, J Sun, S Zhang, FL Fan, Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection

2026

• JIII C He, H Shi, JX Liao, B Liu, Q Liu, J Li, Z Yu, Prior knowledge-embedded first-layer interpretable paradigm for rail transit vehicle human-computer collaboration fault monitoring

• IEEE TR WE Yu, S Zhang, J Sun, JX Liao*, X Zhang, A Class-Aware Supervised Contrastive Quadratic Neural Network for Imbalanced Bearing Fault Diagnosis

• Micromachines Li X, Gao Y, Chen G, Zhang M*, Liao J*, Wang Z, Sun J. A Wearable Multi-Modal Measurement System with Self-Developed IMUs and Plantar Pressure Sensors for Real-Time Gait Recognition.

• Arxiv JX Liao, H Wang, T Li, D Lyu, Y Zhang, C Cai, FL Fan. Big2Small: A Unifying Neural Network Framework for Model Compression.

  2025

• MSSP JX Liao, C He, J Li, J Sun, S Zhang, X Zhang, Classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise, Mechanical Systems and Signal Processing, (ESI High Cited Paper)

• IEEE TPAMI FL Fan, HC Dong, Z Wu, L Ruan, T Zeng, Y Cui, JX Liao*, One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networks

• Remote Sens J Tang, D Liu, Q Wang*, J Li, J Liao, J Sun, Marginal Contribution Spectral Fusion Network for Remote Hyperspectral Soil Organic Matter Estimation

• Arxiv H Pei#, JX Liao#, Q Zhao, T Gao, S Zhang, X Zhang, F Fan, NeuronSeek: On Stability and Expressivity of Task-Driven Neurons

• Arxiv J Fan, Z Hao, J Shen, SL Jui, Y Zhang, JX Liao, FL Fan*, Compress Any Segment Anything Model (SAM)

• RESS C Li, P Dong, Y Jin, JX Liao, SH Chung, C Jiang, X Zhang* Chaos-inspired active learning for physics-informed neural networks to assess the reliability of multi-state systems

2024

• IEEE TII JX Liao , J Li, HC Dong, M Zhang, S Zhang, X Zhang* Logarithmic Cumulative Transformation: A Simple Yet Effective Approach for Bearing Remaining Useful Life Prediction

• IEEE TIM JX Liao, SL Wei, CL Xie, T Zeng, J Sun, S Zhang, X Zhang, FL Fan*, BearingPGA-Net: A Lightweight and Deployable Bearing Fault Diagnosis Network via Decoupled Knowledge Distillation and FPGA Acceleration

• IEEE TAI JX Liao, BJ Hou, HC Dong, H Zhang, X Zhang, J Sun, S Zhang, FL Fan, Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection

• Computers, Materials & Continua M. Zhang, B. Zhao, J. Sun, Q. Wang*, D. Liu, J. Li, J. Liao*, Research on Driver’s Fatigue Detection Based on Information Fusion

• IEEE JBHI XC Zhong, Q Wang, D Liu, Z Chen, J Liao, J Sun, Y Zhang, FL Fan, EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG Classification (ESI High Cited Paper)

2023

• IEEE TIM JX Liao, HC Dong, ZQ Sun, J Sun, S Zhang, FL Fan, Attention-embedded Quadratic Network (Qttention) for Effective and Interpretable Bearing Fault Diagnosis, (ESI High Cited Paper)
• MST JX Liao, HC Dong, L Lou, J Sun, S Zhang*, Multi-task Neural Network Blind Deconvolution and its Application to Bearing Fault Feature Extraction

• Computers in Biology and Medicine XC Zhong, Q Wang*, D Liu, J-X Liao, R Yang, S Duan, G Ding, J Sun, A deep domain adaptation framework with correlation alignment for EEG-based motor imagery classification

• Arxiv HC Dong, Y Jiang, Y Huang, J Liao , B Liu, D Ye, G Liu, Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise

2022

• NeurocomputingH Dong, J Liao , Y Wang, Y Chen, B Liu, D Ye, G Liu*, Training neural networks for solving 1-D optimal piecewise linear approximation

🎖 Honors and Awards

• 2025.09 Outstanding PhD Thesis Nomination Award (TOP 10%), Harbin Institute of Technology
• 2024.11 HIT Merit Student
• 2023.11 Chen Fang Scholarship, Harbin Institute of Technology
• 2023.09 Research Postgraduate Scholarship for Dual Ph.D Programme, The Hong Kong Polytechnic University
• 2018.08 13th The China Graduate Electric Design Contest, National First Prize

📖 Educations

• 2023.09 - 2025.12, Ph.D., Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
• 2021.03 - 2025.08, Ph.D., Instrumentation Science and Technology, Harbin Institute of Technology, Harbin, China
• 2017.09 - 2019.06, M.Eng. (with thesis), Instrumentation Engineering, Harbin Institute of Technology, Harbin, China
• 2013.09 - 2017.07, B.S., Measurement and Control Technology and Instrumentation, Harbin Institute of Technology, Harbin, China

💬 Invited Talks

• 2026.01 “Advancement of Nonlinear Neural Networks.” Huawei, Dongguan, China

• 2025.11 “Uncertainty-Aware Heterogeneous Neural Blind Deconvolution Ensemble Network for Reliable System-Level Fault Diagnosis in Railway Transmission Systems.” The sixth International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence, Guangzhou, China

• 2025.07, “Recently Advancement of Introducing Neural Diversity into Deep Learning.” At International Joint Conference on Neural Networks (IJCNN), Rome, Italy. [Slide]
• 2022.08, “Attention-embedded Quadratic Network (Qttention) for Effective and Interpretable Bearing Fault Diagnosis”. At the 2nd International High-level Forum on High-end Measurement Instruments & 12th International Symposium on Precision Engineering Measurements and Instrumentation (Tier 1 conference in Instrumentation Science), Guilin, China.

👨🏻‍🏫 Teaching

• PolyU: ISE5606 Business Intelligence and Data Mining, 23/24 Spring, Teaching Assistant
• PolyU: ISE328 Technology and Applications of Electronic Business Systems, 24/25 Fall, Teaching Assistant
• PolyU: ENG3004 Society and the Engineer, 24/25 Spring, Teaching Assistant

💻 Work Experiences

• 2025.09 - present, Postdoctoral, Department of Data Science, City University of Hong Kong.
• 2025.09 - 2025.12, Research Assistant, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University.
• 2023.07 - 2023.09, Research Assistant, Department of Mathematics, Chinese University of Hong Kong.
• 2020.08 - 2021.02, Research Assistant, School of Instrumentation Science and Engineering, Harbin Institute of Technology.
• 2019.07 - 2020.07, Control & Navigation Engineer, Chang Hong Machinery Factory.

✍️ Academic Service

• Active Reviewer in TII, TCYB, TFS, MSSP, JBHI, iScience, Neurocomputing, …
• Guest Editor in Signals SI:Advanced Signal Processing Techniques for Modern Artificial Intelligence Systems Submittion Open