Research Description:

Dr. Hackl’s research focuses on complex infrastructure systems, intelligent risk and resilience assessments to climate change, as well as integrated solutions to future challenges facing our cities and society. His research interests lie at the interface between formal methods in network sciences and their integration with prevailing simulation methods, such as digital twins. He is particularly interested in developing scalable data analytics and machine learning techniques for spatial-temporal networks applied to dynamic processes in complex multiscale civil engineered systems to open and interconnect new perspectives for, e.g., modeling of usage, behavior, and performance; analysis of system integration; as well as detection of systemic risks in socio-technical systems. Another aspect of his work covers integrating these data-driven approaches with physics-based models to create digital twins that can learn from and update based on multiple data sources, as well as represent and predict the current and future conditions of their physical counterparts.