Doctoral project Dirk Deschrijver

Context-Aware Deep Learning for Biomedical Time Series Analysis

Deep Learning on Time Series Data for Health Care

Doctoral project Aren Maes

Interpretable Machine Learning for Motor Evoked Potentials and Respiratory Time Series Data

Predictive Models of Time Series Data in Health Care

Quantifying Uncertainty and Improving Reliability of Time-Series Based Deep Learning Models

Time-Series-Based Forecasting of Biomanufacturing Processes

Bayesian Active Learning for Modeling and Optimization of Microwave Devices

Doctoral project Anthony Andrea Faustine

Doctoral project Kyle Powers Foss

Doctoral project Nicolas Knudde

Doctoral project Prashant Singh

Doctoral project Rémi Delanghe

Doctoral project Roberto Medico

Doctoral project Tom Van Steenkiste

Interpretable Machine Learning for Motor Evoked Potentials and Respiratory Time Series Data

Kernel-Aided Rational Macromodeling of LTI Systems

ML-Based Sequential Sampling Techniques for Accelerating EMC Measurements

Physics-Informed Spatio-Temporal Modelling and Robust Optimization for Energy & Utility Management Decision-Making

Towards Machine Learning-Based Predictive Maintenance in Industry Using Vibration and Acoustic Data

Automated Patient Trajectory Prediction of Atrial Fibrillation and other Heart Arrhythmias using Machine Learning on the Standard 12-Lead ECG.

Empowering Healthcare with Trustworthy Event-Based Deep Learning

Machine Learning-based solutions for the prediction of acute COPD exacerbations

Machine Learning for predictive modeling in health care

Non-Invasive Monitoring of Vascular Disease with AI.

Prediction of arrhythmias based on 10-second 12-lead ECG signals

Robuste techniques for multivariate surrogate modeling