Ghent University Academic Bibliography

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- Conference Paper
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Enabling privacy-aware AI-based ergonomic analysis

Sander De Coninck (UGent) , Emilio Gamba, Bart Van Doninck, Abdellatif Bey-Temsamani, Sam Leroux (UGent) and Pieter Simoens (UGent)

(2025) PROCEDIA CIRP. In Procedia CIRP 136. p.371-376
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Automated extraction of competencies for assembly operators from process and product information using a large language model

Serkan Solmaz, Valeriya Skripnik (UGent) , Steven Hoedt (UGent) and Bart Van Doninck

(2024) PROCEDIA CIRP.
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- Journal Article
- A1
- open access
Bayesian multi-objective optimization of process design parameters in constrained settings with noise : an engineering design application

Alejandro Morales Hernández, Sebastian Rojas Gonzalez (UGent) , Inneke Van Nieuwenhuyse, Ivo Couckuyt (UGent) , Jeroen Jordens, Maarten Witters and Bart Van Doninck

(2024) ENGINEERING WITH COMPUTERS. 40(4). p.2497-2511
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Hybrid modeling of an adhesive bonding process, case study : polyphenylene sulfide

Saeideh Khatiry Goharoodi (UGent) , Jeroen Jordens, Bart Van Doninck and Guillaume Crevecoeur (UGent)

(2023) 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT). p.1786-1791
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Multi-objective optimization of adhesive bonding process in constrained and noisy settings

Alejandro Morales-Hernández, Inneke Van Nieuwenhuyse, Sebastian Rojas Gonzalez (UGent) , Jeroen Jordens, Maarten Witters and Bart Van Doninck

(2023) OPTIMIZATION AND LEARNING, OLA 2023. In Communications in computer and information science 1824. p.213-223

Academic Bibliography

Enabling privacy-aware AI-based ergonomic analysis

Automated extraction of competencies for assembly operators from process and product information using a large language model

Bayesian multi-objective optimization of process design parameters in constrained settings with noise : an engineering design application

Hybrid modeling of an adhesive bonding process, case study : polyphenylene sulfide

Multi-objective optimization of adhesive bonding process in constrained and noisy settings

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