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SRIS (Smart, Reliable, and Interpretable Systems) lab is a research group directed by Dr. Gang Chen at South China University of Technology. The main research interest includes machine learning, formal methods, control theory, signal processing and their applications on cyber-physical system monitoring and control.

Recent News


    [Oct 14, 2024] Our paper "Fault tracing in multistage gearbox systems based on an improved transfer path analysis method" has been accepted by Measurement

    [Sept 25, 2024] Our paper "In-situ quality inspection based on coaxial melt pool images for laser powder bed fusion with depth graph network guided by prior knowledge" has been accepted by Mechanical Systems and Signal Processing.

    [July 12, 2024] Our paper "VNCCD: A Gearbox Fault Diagnosis Technique under Nonstationary Conditions via Virtual Decoupled Transfer Paths" has been accepted by Mechanical Systems and Signal Processing.

    [June 29, 2024] Our paper "Enhancing Reliability through Interpretability: A Comprehensive Survey of Interpretable Intelligent Fault Diagnosis in Rotating Machinery" has been accepted by IEEE ACCESS.

    [May 13, 2024] Our paper "Fast Pareto Set Approximation for Multiobjective Flexible Job Shop Scheduling via Parallel Preference-Conditioned Graph Reinforcement Learning" has been accepted by Swarm and Evolutionary Computation.

    [April 30, 2024] Our lab has received a research grant from "State Key Laboratory of Mechanical Transmission for Advanced Equipment, Chongqing University" on wind turbine gearbox fault diagnosis.

    [April 25, 2024] Our paper "Bearing Fault Diagnosis via Robust PCA with Nonconvex Rank Approximation" has been accepted by IEEE Sensors Journal.

    [April 9, 2024] Our paper " Knowledge-Based Clustering Federated Learning for Fault Diagnosis in Robotic Assembly Systems" has been accepted by Knowledge-Based Systems.

    [March 25, 2024] Our paper "Extended Residual Learning with One-shot Imitation Learning for Robotic Assembly in Semi-structured Environment" has been accepted by Frontiers in Neurorobotics.

    [March 18, 2024] Our paper "Task attention-based multimodal policy and curriculum residual learning for context generalization in robotic assembly" has been accepted by Applied Intelligence.

    [Jan 30, 2024] Our paper "A Neural-symbolic Network for Interpretable Fault Diagnosis of Rolling Element Bearings Based on Temporal Logic" has been accepted by IEEE Transactions on Instrumentation and Measurement.

    [Jan 22, 2024] Our paper "Control/Physical Systems Co-design with Spectral Temporal Logic Specifications and Its Applications to MEMS" has been accepted by the International Journal of Control.

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