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Department of Mechanical Engineering
Head of the group

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

© CRE

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

  • 2021 - now: Editor at Mechanical Systems and Signal Processing (link)
  • 2021 - now: Associate Editor at the ASME Open Journal of Engineering (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
  1. 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
  2. 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 
  3. Faes, M., Valdebenito, M. (2020). Fully Decoupled Reliability-Based Design Optimization of Structural Systems Subject to Uncertain Loads. Computer Methods In Applied Mechanics And Engineering371, Art.No. 113313. doi: 10.1016/j.cma.2020.113313
  4. 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
  5. 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 Processing152, Art.No. 107482. doi: 10.1016/j.ymssp.2020.107482