System Reliability

System reliability research focuses on ensuring the dependable operation of complex systems, particularly in critical applications like autonomous vehicles and healthcare. Current efforts concentrate on leveraging AI, specifically machine learning models such as neural networks (including Bayesian and convolutional variants) and ensemble methods, to predict and prevent failures through predictive maintenance and real-time anomaly detection. This work is crucial for improving the safety and efficiency of various technological systems, impacting both the development of robust AI and the reliability of the infrastructure they support.