Prof. Dr. Daniel Straub
Academic Career and Research Areas
Professor Straub develops and teaches risk and reliability analysis for engineering systems. He combines probabilistic modeling, data analysis, decision theory and artificial intelligence methods to a modern risk assessment approach. A core interest of Professor Straub lies in the use of dynamic information (e.g. from sensors and monitoring systems) for risk assessment. This includes developing algorithms for rare (extreme) events and quantifying the value of information from monitoring systems. He is also working on managing risk and reliability of complex and autonomous systems. His portfolio of research and industry consulting includes applications to structural design and assessment, offshore and marine engineering, geotechnical engineering, natural hazards, automotive as well as aero- and astronautics.
Professor Straub received his diploma (2000) and doctorate (2004) from ETH Zurich. He subsequently worked at UC Berkeley before joining TUM in 2008. Throughout his career, he has been active as a consultant to the industry. Professor Straub has executive roles in international bodies in the field of engineering risk and is a frequent keynote speaker at major conferences. He is also an Honorary Professor at the University of Aberdeen, UK.
- Early Achievement Research Award, International Association for Structural Safety and Reliability IASSAR (2013)
- SNF Fellowship für fortgeschrittene Forscher (2006-2008)
- Silbermedaille der ETH Zürich (2005)
- Rene Hornung-Medaille der SGZfP (2005)
Key Publications (all publications)
Straub D, Papaioannou I, Betz W: “Bayesian analysis of rare events”. Journal of Computational Physics. 2016; 314: 538–556.Abstract
Straub D, Papaioannou I: “Bayesian Updating with Structural Reliability Methods”. Journal of Engineering Mechanics. Trans. ASCE. 2015; 141(3): 04014134.
Straub D: “Value of information analysis with structural reliability methods”. Structural Safety. 2014; 49:75-86.Abstract
Straub D, Der Kiureghian A: „Bayesian Network Enhanced with Structural Reliability Methods. Part A: Theory & Part B: Applications. Journal of Engineering Mechanics. Trans. ASCE. 2010; 136(10): 1248-1270.Abstract
Straub D: “Stochastic modeling of deterioration processes through dynamic Bayesian networks”. Journal of Engineering Mechanics, Trans. ASCE. 2009; 135(10): 1089-1099.Abstract