Operational Risk

Operational risk assessment focuses on quantifying and mitigating the likelihood and impact of undesirable events within complex systems. Current research emphasizes the development of efficient predictive models, particularly leveraging graph neural networks and deep reinforcement learning, to forecast system states and assess risks in diverse domains such as power grids and healthcare. These advancements aim to improve situational awareness and decision-making by providing faster, more accurate risk estimations than traditional methods, ultimately enhancing safety and operational efficiency across various industries. The improved accuracy and speed of these models are particularly valuable in time-sensitive applications requiring real-time risk assessment.