Network Resilience

Network resilience research focuses on understanding and enhancing the ability of systems, from transportation networks to online services, to withstand disruptions and maintain functionality. Current efforts involve developing mathematical models and optimization algorithms, often incorporating machine learning techniques like deep learning and graph-based methods, to predict resilience, identify vulnerabilities, and design mitigation strategies. This work is crucial for improving the robustness of critical infrastructure and ensuring the reliable operation of complex systems across various sectors, impacting fields ranging from cybersecurity to supply chain management. The development of more accurate predictive models and effective resource allocation strategies is a key focus.