Aarhus University Seal / Aarhus Universitets segl

Umberto Alibrandi

Associate Professor

Umberto Alibrandi
See relations at Aarhus University


I graduated as PhD in Civil and Environmental Engineering, at the University of Messina, 2006, defending the thesis “Computational Methods in Structural Reliability and Stochastic Mechanics”. I was postdoctoral researcher at the University of Messina from 2006 to 2008, University of California at Berkeley from September 2008 to May 2009, National University of Singapore from 2013 to 2015, Nanyang Technological University from 2015 to 2017, and Berkeley Education Alliance for Research in Singapore from 2017 to 2018. From 2010 to 2012, I worked as a Structural Engineer in Italy. I apply methods of Performance Based Engineering, Structural Reliability, and Risk Analysis, Computational Stochastic Mechanics, Risk informed Decision Support for structures, Machine Learning, and Artificial Intelligence for academia and industry for more than 15 years. I have been involved in research projects focused on risk analysis of offshore systems, risk management of resilient transportation networks, sustainable and resilient design of smart buildings/infrastructures. Within these areas, I have lectured classes since 2003, and I have published over 60 papers in high-ranking scientific journals and international conference proceedings.

My current research interests focus on the development of new data-driven risk-based frameworks, methods, and tools aimed at sustainable and resilient urban communities. This requires incorporating holistically urban systems, energy systems, environmental systems, and human systems. More specifically, to cope with the inherent complexity and uncertainty, I am developing a novel framework of data-driven uncertainty quantification and risk analysis rooted on the information theory. 

The framework will be tailored to the deployment of Risk-informed Digital Twins (RDT) for design and management under uncertainty of smart buildings and infrastructures. The tools of the RDT are going to be deployed inside the opensource computational platform OpenAIUQ. 

View all (61) »

View all (13) »

View all (4) »

Latest activities and conferences

ID: 134645422