Computing System

Computing systems research currently focuses on improving efficiency, transparency, and ethical considerations within increasingly complex architectures. Key areas include developing lightweight, unsupervised methods for real-time anomaly detection in large-scale systems, often employing machine learning models like graph neural networks to optimize resource allocation and performance prediction. This work is crucial for enhancing the reliability, security, and accountability of computing systems across diverse applications, from autonomous vehicles to large-scale data centers, and addresses growing concerns about the ethical implications of ubiquitous computing.