Prof. Dr. Matthias G.R. Faes
Email: matthias[dot]faes[at]tu-dortmund[dot]de
Tel.: +49 231 755 6831
Room: Maschinenbaugebäude 1, Raum U03
Office hours: after prior appointment (via Mrs. Georgii)
Zoom: Link
Google Scholar: Link
ResearchGate: Link
Research interests
- Inverse methods for uncertainty quantification, including interval techniques as well as Bayesian model updating schemes
- Advanced numerical propagation schemes for uncertainty analysis and quantification
- Reliability analysis and reliability based design optimization under scarce data
- Imprecise probabilistic concepts for robust uncertainty quantification
Teaching
Introduction Reliability Analysis
Advanced methods for Reliability Analysis
Quality Management
Computational methods (not only) for engineers
Further information
- 2009 - 2012: Bachelor of Science in Engineering Technology - Manufacturing Engineering (finished magna cum laude) at the Lessius University of Applied Sciences, St.-Katelijne-Waver, Belgium.
- 2012 - 2013: Master of Science in Engineering Technology - Manufacturing Engineering (finished summa cum laude) at the Thomas More University of Applied Sciences. St.-Katelijne-Waver, Belgium. Dissertation title: Extrusion based Additive Manufacturing of ceramic components
- 2013 - 2017: Research Associate, doctoral student in Engineering Technology at the KU Leuven, Department of Mechanical Engineering (graduated 10.2017).
- 2017 - 2018: Postdoctoral fellow in the R2D Group at the KU Leuven, Department of Mechanical Engineering
- 2018 - 2022: Postdoctoral fellow of the Flemish Research Foundation, working at the R2D Group
- 2020 - 2022: Postdoctoral fellow of the Alexander von Humboldt foundation at the Institute for Risk and Reliability of the Leibniz University in Hannover
- Since 02.2022: Full Professor in Reliability Engineering at the Faculty of Mechanical Engineering, TU Dortmund University
Editorial work and representation
- 2024 - now: Associate Editor at Mechanical Systems and Signal Processing (link)
- 2021 - now: Associate Editor at the ASME Open Journal of Engineering (link)
- 2021 - 2024: Editor board member at Mechanical Systems and Signal Processing (link)
- 2022 - now: Associate Managing Editor at the ASCE/ASME Journal for Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering (link)
- 2022 - now: Associate Managing Editor at the ASCE/ASME Journal for Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
- 2021 – now: Full member of the American Society of Civil Engineers
- 2022 – now: Full Member of the American Society of Mechanical Engineers
- 2023 – now: Executive board member of the European Society for Structural Dynamics
- 2022: International Technical Committee Chair ISRERM 2022
- 2023: Scientific Committee member of UNCECOMP2023
Awards
- 2023 - World's top 2% scientists according to Stanford's list (link)
- 2023 - EASD Junior Research Prize in the Area of Development of Methodologies for Structural Dynamics. European Association of Structural Dynamics.
- 2022 - 'Top Cited Article 2020-2021' in the International Journal for Numerical Methods in Engineering
- 2020 - Willy Asselman Foundation: Award for research excellence in honor of em. Prof. Willy Asselman, honoring excellent young researchers at Campus De Nayer of KU Leuven
- 2019 - SIPTA: IJAR Young Researcher Award for research excellence in imprecise probabilities (link)
- 2018 - ECCOMAS: ECCOMAS Award for the two best Ph.D. theses in 2017 on computational methods in applied sciences and engineering in Europe (link)
- 2018 - BNCTAM: Laureate of the Award for the Best PhD Thesis of 2017 by the Belgian National Committe for Theoretical and Applied Mechanics
- 2016 - CIRP, JSEME: Excellent paper award and semi-plenary lecture during the ISEM XVIII conference on Electro Physical and Chemical Machining
- Faes M., Moens D. (2019). Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty. Archives of Computational Methods in Engineering 1-39. doi: 10.1007/s11831-019-09327-x.
- Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., Moens, D. (2019). A multivariate interval approach for inverse uncertainty quantification with limited experimental data. Mechanical Systems and Signal Processing, 118, 534-548. doi: 10.1016/j.ymssp.2018.08.050
- Faes, M., Valdebenito, M. (2020). Fully Decoupled Reliability-Based Design Optimization of Structural Systems Subject to Uncertain Loads. Computer Methods In Applied Mechanics And Engineering, 371, Art.No. 113313. doi: 10.1016/j.cma.2020.113313
- Faes, M., Daub, M., Marelli, S., Patelli, E., Beer, M. (2021). Engineering analysis with probability boxes: a review on computational methods. Structural Safety, Art.No. 102092. doi: 10.1016/j.strusafe.2021.102092
- Faes, M., Valdebenito, M.A., Moens, D., Beer, M. (2021). Operator norm theory as an efficient tool to propagate hybrid uncertainties and calculate imprecise probabilities. Mechanical Systems And Signal Processing, 152, Art.No. 107482. doi: 10.1016/j.ymssp.2020.107482