The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Daniel Straub sits on this spectrum.
This scientist: 348 publications — 83rd percentile
83% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 804 publications or more.
The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Daniel Straub sits on this spectrum.
This scientist: 51 D-Index — 62nd percentile
62% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 107 D-Index or more.
Daniel Straub is affiliated with the Technical University of Munich in Germany. Their research primarily focuses on engineering and decision sciences, with an emphasis on topics related to probabilistic and robust engineering design, reliability and maintenance optimization, and structural health monitoring techniques.
The scientist's work spans several subfields including statistics, probability and uncertainty, civil and structural engineering, safety, risk, reliability and quality, statistics and probability, as well as mechanics of materials. This multidisciplinary approach reflects in the range of their recent research outputs and collaborations.
Daniel Straub has contributed to numerous publications, with a notable presence in several key academic venues. Frequent publication platforms include:
Recent papers authored or co-authored by Daniel Straub highlight advances in structural health monitoring, reliability analysis, and Bayesian model updating. Selected works include:
The scientist collaborates frequently with several researchers. Common co-authors include:
Daniel Straub's research interest also covers areas such as infrastructure maintenance and monitoring, concrete corrosion and durability, risk and safety analysis, and fatigue and fracture mechanics. This broad thematic scope supports a data-driven and probabilistic approach to engineering challenges.
Iason Papaioannou;Wolfgang Betz;Kilian Zwirglmaier;Daniel Straub
Daniel Straub;Iason Papaioannou
Wolfgang Betz;Iason Papaioannou;Daniel Straub
Daniel Straub;Michael Havbro Faber
Daniel Straub
Iason Papaioannou;Costas Papadimitriou;Daniel Straub
Daniel Straub;Armen Der Kiureghian
Daniel Straub
Daniel Straub;Daniel Straub;Armen Der Kiureghian;Armen Der Kiureghian
Daniel Straub
Adrienne Grêt-Regamey;Daniel Straub
Daniel Straub
Michelle Bensi;Armen Der Kiureghian;Daniel Straub
Wolfgang Betz;Iason Papaioannou;Daniel Straub
Martina Sättele;Michael Bründl;Daniel Straub
D. Straub
Unknown
Shui-Hua Jiang;Shui-Hua Jiang;Iason Papaioannou;Iason Papaioannou;Daniel Straub;Daniel Straub
Iason Papaioannou;Daniel Straub
Jesus Luque;Daniel Straub
Daniel Straub;Daniel Straub;Armen Der Kiureghian;Armen Der Kiureghian
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