Trustworthy AI for Intelligent Systems

构建智能、可靠、可解释的系统。

SRIS Lab integrates logic, physics, and learning to build trustworthy intelligent systems for advanced manufacturing, safety-critical autonomy, and health-aware infrastructure.

Our methodology unifies 信号时序逻辑, causal inference, and physics-guided priors to support interpretable diagnosis, verifiable machine learning, safe autonomy, and fleet-level prognostics.

查看研究方向 查看成果
Neuro-symbolic AI Physics-guided diagnosis Safe robot autonomy
SRIS实验室 SCUT · GZIC
Logic + Learning
Interpretable and certifiable AI pipelines
智能运维
Diagnosis, prediction, and decision-making
机器人
Safe autonomy and human-centered systems
重大系统
Manufacturing and infrastructure applications
South China University of Technology · Guangzhou International Campus
Research philosophy
From formal semantics to deployable engineering systems
Method stack
Temporal logic · Causality · Physics-guided learning
Application domains
Manufacturing, robotics, PHM, and resilient infrastructure
Lab value
Interpretability, reliability, and safety by design
Research Thrusts

三个紧密耦合的研究方向

01 · Foundations

神经符号基础模型

融合逻辑约束、因果结构与学习表征，构建可信工业智能。

  • STL-regularized pretraining and rule distillation
  • Machine-checkable rationales and audit-ready outputs
  • Scalable multimodal learning with structured priors
02 · Diagnosis

因果逻辑预测与健康管理

结合物理引导特征与时序逻辑抽象，重构退化路径并支撑干预决策。

  • Fault propagation tracing across components and fleets
  • Interpretable diagnosis with causal and temporal evidence
  • Cost-aware maintenance decision support
03 · Safe Autonomy

STL驱动的安全机器人与自主系统

面向移动操作、人机协作机器人和具身智能系统的安全优先规划与控制框架。

  • Contract-based planning and control synthesis
  • Reference governors, CBFs, and residual RL
  • Fast deployment under explicit safety guarantees
Lab Highlights

研究、团队与系统的一体化视觉叙事。

轮播区不应只是普通图片集合，而应在一瞥之间传达研究环境、技术定位与应用价值。

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Campus & TeamEnvironment and academic community
MethodsLogic, learning, and physics integration
系统From algorithms to deployable platforms
ImpactTrustworthy intelligence for engineering
  • Graduation and Campus View
    Academic Community

    Graduation and Lab Culture

    华南理工大学充满活力的研究环境，连接人才、思想与跨学科合作。

  • Neuro-Symbolic Foundations
    Methodology

    神经符号基础

    Multimodal representation learning guided by temporal logic, causal structure, and machine-verifiable semantics.

  • STL-Driven Safe Autonomy
    Autonomy

    STL-Driven Safe Autonomy

    规划 and control synthesized under temporal-logic contracts for safe and efficient embodied intelligence.

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