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Deep learning and generative artificial intelligence for predictive maintenance of industrial equipment

Deep reinforcement learning for drilling planning in Oil and Gas projects

Energy efficient process planning and scheduling of flexible manufacturing systems

Resilience of critical infrastructures exposed to climate change

Integration of AI in the probabilistic modelling of pollutant transport for the risk assessment of aquifer contamination from industrial activities

Development of interpretable and trustworthy PHM methods for complex energy systems

Multi-fidelity gray-box models for the computanional risk assessment of cyber-physical systems

Development of XAI methods for PHM of energy systems and components

Trustworthy artificial intelligence for predictive maintenance of industrial equipment

Reliability analysis of telecommunication network

Real-time monitoring methods for the state of power equipment based on data and AI-driven technologies

Human reliability analysis in manned deep submergence operation system

Application of machine learning to high-demand systems, considering uncertainty and interpretability

Dynamic Probabilistic Risk Assessment considering safety barriers degradation

Advanced probabilistic black-box modelling methods for relaibility and risk analysis of new-generation NPPs

Causal discovery and Bayesian optimization

Condition-based risk-informed decison making framework for Severe Accident Management in NPPs

Artificial Intelligence and Stochastic Simulations for the Resilience of Critical Infrastructures

Novel Uncertainty-aware Methods for Remaining Useful Life Prediction of Complex Systems

Application of deep learning methods for state of health estimation and remaining useful life prediction of lithium-ion batteries

Traffic risk and reliability analysis considering intelligent transportation systems and driving behaviours modelling and prediction

Key technology of digital twin model of steam generator

Domain adaptation for critical heat flux prediction