David Moens

Joined

May 2023

Names

David Moens (Preferred)

Emails

****@kuleuven.be (Confirmed)

Personal Links

Google Scholar

DBLP

ORCID

Career & Education History

Associate Professor

KU Leuven (kuleuven.be)

2019 – 2023

Assistant Professor

KU Leuven (kuleuven.be)

2014 – 2019

Postdoc

KU Leuven (kuleuven.be)

2004 – 2014

Advisors, Relations & Conflicts

Coauthor

Hans Hallez

2022 – Present

Coauthor

Keivan Shariatmadar

2021 – Present

PhD Advisor

Kaizheng Wang

2021 – 2025

Expertise

uncertainty quantification

2000 – 2023

structural dynamics

1997 – 2023

numerical modelling in engineering

1997 – 2023

Publications

Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez
- ICLR 2025 Spotlight
- Readers: Everyone
Credal Deep Ensembles for Uncertainty Quantification
Kaizheng Wang, Fabio Cuzzolin, Shireen Kudukkil Manchingal, Keivan Shariatmadar, David Moens, Hans Hallez
- NeurIPS 2024 poster
- Readers: Everyone
An introduction to optimization under uncertainty - A short survey
Keivan Shariatmadar, Kaizheng Wang, Calvin R. Hubbard, Hans Hallez, David Moens
- Published: 01 Jan 2022, Last Modified: 13 May 2023
- CoRR 2022
- Readers: Everyone
Computationally Efficient Optimization Method to Quantify the Required Surgical Accuracy for a Ligament Balanced TKA
Laura Bartsoen, Matthias G. R. Faes, Mariska Wesseling, Roel Wirix-Speetjens, David Moens, Ilse Jonkers, Jos Vander Sloten
- Published: 01 Jan 2021, Last Modified: 17 May 2023
- IEEE Trans. Biomed. Eng. 2021
- Readers: Everyone
A fast inverse approach for the quantification of set-theoretical uncertainty
Lars Bogaerts, Matthias G. R. Faes, David Moens
- Published: 01 Jan 2019, Last Modified: 17 May 2023
- SSCI 2019
- Readers: Everyone
Hybrid spatial uncertainty analysis for the estimation of imprecise failure probabilities in Laser Sintered PA-12 parts
Matthias G. R. Faes, Ghosh Dastidar Sabyasachi, David Moens
- Published: 01 Jan 2019, Last Modified: 17 May 2023
- Comput. Math. Appl. 2019
- Readers: Everyone
Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure
Matteo Broggi, Matthias G. R. Faes, Edoardo Patelli, Yves Govers, David Moens, Michael Beer
- Published: 01 Jan 2017, Last Modified: 17 May 2023
- SSCI 2017
- Readers: Everyone

David Moens

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification

Credal Deep Ensembles for Uncertainty Quantification

An introduction to optimization under uncertainty - A short survey

Computationally Efficient Optimization Method to Quantify the Required Surgical Accuracy for a Ligament Balanced TKA

A fast inverse approach for the quantification of set-theoretical uncertainty

Hybrid spatial uncertainty analysis for the estimation of imprecise failure probabilities in Laser Sintered PA-12 parts

Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure

Co-Authors