Martijn Oldenhof

University of Twente — Netherlands

Computer Science · Physical Sciences

6h-index264citations26works2.12yr avg
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Research Topics

Computational Drug Discovery Methods(6), Machine Learning in Materials Science(5), Simulation Techniques and Applications(4), Model-Driven Software Engineering Techniques(4), Biosimilars and Bioanalytical Methods(4)

Publications26 total

Personalized federated learning for predicting disability progression in multiple sclerosis using real-world routine clinical data
npj Digital Medicine·2025· 4 citedOpen Access
The development of scour holes in lowland rivers: A review on the hydrodynamic and geotechnical conditions
2025
The Behaviour of Deep Scour Holes in Rivers: Stable States or Dynamic Fluctuations?
2025Open Access
Scour Hole Behaviour: A Field Study of the Dutch Rhine Delta
SSRN Electronic Journal·2025Open Access
Accessible Ecosystem for Clinical Research (Federated Learning for Everyone): Development and Usability Study
JMIR Formative Research·2024· 9 citedOpen Access
Atom-Level Optical Chemical Structure Recognition with Limited Supervision
2024· 2 citedOpen Access
Atom-Level Optical Chemical Structure Recognition with Limited Supervision
arXiv (Cornell University)·2024Open Access
Accessible Ecosystem for Clinical Research (Federated Learning for Everyone): Development and Usability Study (Preprint)
2023Open Access
MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information
Journal of Chemical Information and Modeling·2023· 94 citedOpen Access
Industry-Scale Orchestrated Federated Learning for Drug Discovery
Proceedings of the AAAI Conference on Artificial Intelligence·2023· 37 citedOpen Access
Conformal efficiency as a metric for comparative model assessment befitting federated learning
Artificial Intelligence in the Life Sciences·2023· 5 citedOpen Access
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection
arXiv (Cornell University)·2023Open Access
Industry-Scale Orchestrated Federated Learning for Drug Discovery
arXiv (Cornell University)·2022· 10 citedOpen Access
MELLODDY: cross pharma federated learning at unprecedented scale unlocks benefits in QSAR without compromising proprietary information
2022· 24 citedOpen Access
Conformal efficiency as a metric for comparative model assessment befitting federated learning
2022· 4 citedOpen Access
MELLODDY-Predictor Software input files
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
MELLODDY-Predictor Software input files
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
MELLODDY Model Manipulation Software input files
2022Open Access
MELLODDY Model Manipulation Software input files
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
MELLODDY Model Manipulation Software input files
2022Open Access
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Frequent Co-authors

Yves Moreau(15), Ádám Arany(13), Lukas Friedrich(12), Jaak Simm(9), Fabien Gelus(8), Adrien Darbier(8), Alexandre Picosson(8), Lewis Mervin(6), Noé Sturm(6), Adam Zalewski(6), Peter Schmidtke(6), Hugo Ceulemans(6), Edward De Brouwer(6), Wouter Heyndrickx(5), Ansgar Schuffenhauer(5), Lina Humbeck(4), Ritsuya Niwayama(4), Arina Afanasyeva(4), Régis Loeb(4), Maria Teleńczuk(4)