Maximin and Maximal Solutions for Linear Programming Problems with Possibilistic Uncertainty. - Erik Quaeghebeur; Nathan Huntley; Keivan Shariatmadar; Gert de Cooman (IPMU (3), 2012)

Constrained optimization problems under uncertainty with coherent lower previsions. - Erik Quaeghebeur; Keivan Shariatmadar; Gert de Cooman (Fuzzy Sets Syst., 2012)

Linear programming under p-box uncertainty model. - Keivan Shariatmadar; Mark Versteyhe (ICCMA, 2019)

Methodology for a Gradual Migration from a Centralized towards a Decentralized Control in AGV Systems. - Matthias De Ryck; Mark Versteyhe; Keivan Shariatmadar (ICMRE, 2020)

CMMSE: Linear programming under ϵ-contamination uncertainty. - Keivan Shariatmadar; Matthias De Ryck; Kristof Driesen; Frederik Debrouwere; Mark Versteyhe (Comput. Math. Methods, 2020)

Numerical Linear Programming under Non-Probabilistic Uncertainty Models - Interval and Fuzzy Sets. - Keivan Shariatmadar; Mark Versteyhe (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2020)

Design and Calibration of an Instrumented Seat Post to Measure Sitting Loads While Cycling. - Dieltiens Sien; D'hondt Jordi; Marc Juwet; Keivan Shariatmadar; Mark Versteyhe (Sensors, 2020)

An introduction to optimization under uncertainty - A short survey. - Keivan Shariatmadar; Kaizheng Wang; Calvin R. Hubbard; Hans Hallez; David Moens (CoRR, 2022)

Path Planning Problem under non-probabilistic Uncertainty. - Keivan Shariatmadar (CoRR, 2022)

Random-Set Convolutional Neural Network (RS-CNN) for Epistemic Deep Learning. - Shireen Kudukkil Manchingal; Muhammad Mubashar; Kaizheng Wang; Keivan Shariatmadar; Fabio Cuzzolin (CoRR, 2023)

Credal Deep Ensembles for Uncertainty Quantification. - Kaizheng Wang; Fabio Cuzzolin; Shireen Kudukkil Manchingal; Keivan Shariatmadar; David Moens; Hans Hallez (NeurIPS, 2024)

Credal Wrapper of Model Averaging for Uncertainty Estimation on Out-Of-Distribution Detection. - Kaizheng Wang; Fabio Cuzzolin; Keivan Shariatmadar; David Moens; Hans Hallez (CoRR, 2024)

Generalisation of Total Uncertainty in AI: A Theoretical Study. - Keivan Shariatmadar (CoRR, 2024)

Random-Set Neural Networks. - Shireen Kudukkil Manchingal; Muhammad Mubashar; Kaizheng Wang; Keivan Shariatmadar; Fabio Cuzzolin (ICLR, 2025)

Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification. - Kaizheng Wang; Fabio Cuzzolin; Keivan Shariatmadar; David Moens; Hans Hallez (ICLR, 2025)

Most likely heteroscedastic Gaussian process via kernel smoothing. - Ghifari Adam Faza; Nasrulloh R. B. S. Loka; Keivan Shariatmadar; Hans Hallez; David Moens (Knowl. Based Syst., 2025)

CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks. - Kaizheng Wang; Keivan Shariatmadar; Shireen Kudukkil Manchingal; Fabio Cuzzolin; David Moens; Hans Hallez (Neural Networks, 2025)

Generalized Decision Focused Learning under Imprecise Uncertainty-Theoretical Study. - Keivan Shariatmadar; Neil Yorke-Smith; Ahmad Osman; Fabio Cuzzolin; Hans Hallez; David Moens (CoRR, 2025)

AI-Enhanced Precision in Sport Taekwondo: Increasing Fairness, Speed, and Trust in Competition (FST.ai). - Keivan Shariatmadar; Ahmad Osman (CoRR, 2025)