portfolio
publications
Patient activity recognition using radar sensors and machine learning
Published in Neural Computing and Applications, 2022
Recommended citation: "Patient activity recognition using radar sensors and machine learning." Neural Computing and Applications, 2022.
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Split BiRNN for real-time activity recognition using radar and deep learning
Published in Scientific Reports, 2022
Recommended citation: "Split BiRNN for real-time activity recognition using radar and deep learning." Scientific Reports, 2022.
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Uncertainty quantification for appliance recognition in non-intrusive load monitoring using Bayesian deep learning
Published in Energy and Buildings, 2022
Recommended citation: "Uncertainty quantification for appliance recognition in non-intrusive load monitoring using Bayesian deep learning." Energy and Buildings, 2022.
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Convolutional Neural Networks for Apnea Detection from Smartphone Audio Signals: Effect of Window Size
Published in Proceedings of IEEE EMBC 2022, 2022
Recommended citation: "Convolutional Neural Networks for Apnea Detection from Smartphone Audio Signals: Effect of Window Size." In the proceedings of 2022 44th Annual International Conference of the IEEE Engineering in Medicine &amp$mathsemicolon$ Biology Society (EMBC), 2022.
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Quantifying Uncertainty in Real Time with Split BiRNN for Radar Human Activity Recognition
Published in the proceedings of 2022 19th European Radar Conference (EuRAD), 2022
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Recommended citation: "Quantifying Uncertainty in Real Time with Split BiRNN for Radar Human Activity Recognition." In the proceedings of 2022 19th European Radar Conference (EuRAD), 2022.
Tailoring Radar-Based Patient Monitoring Models to Real-Life Needs using Utility Maximization
Published in the proceedings of 2022 19th European Radar Conference (EuRAD), 2022
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Recommended citation: "Tailoring Radar-Based Patient Monitoring Models to Real-Life Needs using Utility Maximization." In the proceedings of 2022 19th European Radar Conference (EuRAD), 2022.
Open-set patient activity recognition with radar sensors and deep learning
Published in IEEE Geoscience and Remote Sensing Letters, 2023
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Recommended citation: "Open-set patient activity recognition with radar sensors and deep learning." IEEE Geoscience and Remote Sensing Letters, 2023.
Reliable assessment of uncertainty for appliance recognition in NILM using conformal prediction
Published in Electronics Letters, 2023
Use Google Scholar for full citation
Recommended citation: "Reliable assessment of uncertainty for appliance recognition in NILM using conformal prediction." Electronics Letters, 2023.
Data-Driven Surrogate Modeling for the Flammability Reduction System
Published in the proceedings of AIAA SCITECH 2024 Forum, 2024
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Recommended citation: "Data-Driven Surrogate Modeling for the Flammability Reduction System." In the proceedings of AIAA SCITECH 2024 Forum, 2024.
Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center study
Published in PLOS Digital Health, 2024
Recommended citation: Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center study. PLOS Digital Health, 2024.
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Towards Trustworthy Neural Networks for Certification by Analysis–Fuel Tank Flammability Reduction System
Published in the proceedings of FrontUQ2024, Workshop on Frontiers of Uncertainty Quantification, 2024
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Recommended citation: "Towards Trustworthy Neural Networks for Certification by Analysis--Fuel Tank Flammability Reduction System." In the proceedings of FrontUQ2024, Workshop on Frontiers of Uncertainty Quantification, 2024.
Optimized Data Transmission for Radar-Based Edge-Cloud Human Activity Recognition via Quantization
Published in the proceedings of 2024 21st European Radar Conference (EuRAD), 2024
Use Google Scholar for full citation
Recommended citation: "Optimized Data Transmission for Radar-Based Edge-Cloud Human Activity Recognition via Quantization." In the proceedings of 2024 21st European Radar Conference (EuRAD), 2024.
Optimizing Memory Footprint for Radar-Based Human Activity Recognition on Resource-Constrained Devices
Published in the proceedings of 2024 21st European Radar Conference (EuRAD), 2024
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Recommended citation: "Optimizing Memory Footprint for Radar-Based Human Activity Recognition on Resource-Constrained Devices." In the proceedings of 2024 21st European Radar Conference (EuRAD), 2024.
Deep Learning-Based Event Counting for Apnea-Hypopnea Index Estimation using Recursive Spiking Neural Networks
Published in IEEE Transactions on Biomedical Engineering, 2024
Selected as a featured article in April 2025 (https://www.embs.org/tbme/articles/deep-learning-based-event-counting-for-apnea-hypopnea-index-estimation-using-recursive-spiking-neural-networks/)
Recommended citation: "Deep Learning-Based Event Counting for Apnea-Hypopnea Index Estimation using Recursive Spiking Neural Networks." IEEE Transactions on Biomedical Engineering, 2024.
The Role of Trustworthy and Reliable AI for Multiple Sclerosis
Published in Frontiers in Digital Health, 2025
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Recommended citation: "The Role of Trustworthy and Reliable AI for Multiple Sclerosis." Frontiers in Digital Health, 2025.
Leveraging Hand-Crafted Radiomics on Multicenter FLAIR MRI for Predicting Disability Progression in People with Multiple Sclerosis
Published in Frontiers in Neuroscience, 2025
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Recommended citation: "Leveraging Hand-Crafted Radiomics on Multicenter FLAIR MRI for Predicting Disability Progression in People with Multiple Sclerosis." Frontiers in Neuroscience, 2025.
Ising Machines for Model Predictive Path Integral-Based Optimal Control
Published in NeurIPS Workshop: 2nd edition of Frontiers in Probabilistic Inference: Learning meets Sampling, 2025
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Recommended citation: "Ising Machines for Model Predictive Path Integral-Based Optimal Control." In NeurIPS Workshop: 2nd edition of Frontiers in Probabilistic Inference: Learning meets Sampling, 2025.
Combining Magnetic Resonance Imaging and Evoked Potentials Enhances Machine Learning Prediction of Multiple Sclerosis Disability Worsening
Published in Frontiers in Immunology, 2026
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Recommended citation: "Combining Magnetic Resonance Imaging and Evoked Potentials Enhances Machine Learning Prediction of Multiple Sclerosis Disability Worsening." Frontiers in Immunology, 2026.
Data-driven hypothesis discovery from disease trajectories in multiple sclerosis
Published in Frontiers in Immunology, 2026
Use Google Scholar for full citation
Recommended citation: "Data-driven hypothesis discovery from disease trajectories in multiple sclerosis." Frontiers in Immunology, Volume 17, 2026.
talks
Trustworthy ML for Healthcare: Challenges and Developments
Published:
In this talk, we will discuss trustworthy ML (TML) and what it entails. We will explore the key challenges in ensuring TML in healthcare settings, such as data privacy, algorithmic bias, and model interpretability. Additionally, the talk will cover recent developments and strategies to overcome these challenges, emphasizing the importance of building reliable AI systems to improve patient outcomes and trust in healthcare technology.
Trustworthy and Reliable (Deep) Machine Learning for Healthcare
Published:
As machine learning (ML) models are increasingly used in daily life, their trustworthiness is called into question. Large Language Models have put this into focus in the past few years. In this lecture, the different ways to achieve trust in healthcare will be covered, as well as remaining challenges.
teaching
Computer Science (nl: Informatica)
Undergraduate course, Ghent University, Department of Computer Science, 2019
His responsibilities included leading lab sessions, providing one-on-one mentoring, and troubleshooting technical issues.