DrLorenzo Jr Sabug

Lorenzo Sabug, Jr. is a research associate at Imperial College, and is co-investigator of UKRI EPSRC grant "Concurrent Learning and Control of Uncertain Large-Scale Phenomena". He performs theoretical and methodological research on physics-informed machine learning and dual control, and their applications on propagation-based phenomena. In his previous work with Politecnico di Milano, he investigated mathematical and data-driven optimization methods, as well as their applications on industrial and aerospace fields. In his Ph.D. research, he designed a new data-driven optimization algorithm framework based on the Set Membership approach, which has been applied in different difficult simulation- and experiment-based engineering design problems, and is available as an open-source toolbox at https://bit.ly/SMGOToolbox.