Hybrid AI and Uncertainty Quantification for Trustworthy Time-to-Event Predictions

Advancing Time Series Data Analytics and Applied Machine Learning in Healthcare

AI for Predictive Healthcare

AI for therapeutic diagnostics

Automatic Detection of Parasites in Stool and Blood Smear Images using Trustworthy Machine Learning

Automatic Detection of Pulmonary Tuberculosis in Chest X-ray Images Using Trustworthy Machine Learning

Context Aware Deep Learning for Predictive Healthcare

Context-Aware Health Monitoring

Context-Aware Machine Learning for Scalable IoT Data Analytics and Visualization Using Semantic Web Technologies

Design and development of an AI-driven digital pathology device

Design of a Deep Patient Model for Improved Outcome Prediction and Medical Decision Support

Doctoral project Colin Soete

Doctoral project Emiel Deprost

Doctoral project Jarne Verhaeghe

Doctoral project Jonas Van Der Donckt

Doctoral project Matthias Van Onsem

Doctoral project Nathan Vandemoortele

Doctoral project Pieter Moens

Doctoral project Sander Vanden Hautte

Doctoral project Thomas Kok

Efficient Insight Mining for Time Series Data in Large Scale Network Monitoring Environments

Hybrid AI for Veterinary Health (Image) Data

Predictive Healthcare

Predictive Maintenance and Data-Driven Diagnostics

Realizing Real-World and Context-Aware Human Behavior Monitoring Using Wearable and Smartphone Data for Mobile Health

Scalable Data Processing Architectures and Machine Learning Solutions for Real-Time Monitoring of Stress

Spatio-temporal enrichment and hybrid machine learning

Towards Personalized Healthcare by Enabling Machine Learning-Driven Agents across Solid Pods

A hybrid machine learning/pharmacokinetic approach to optimize drug dosing in special patient populations

AI for Personalised Healthcare

Antimicrobial stewardship in the intensive care unit: evolving challenges and data science opportunities

Doctoral project Nicolas Vandenbussche

Doctoral project Samnang Nop

Fusing Semantics and Machine Learning for Optimized Building Management

Hybrid AI for chronic disease management

Hybrid Physics-Based Neural Network Models for Predicting Nonlinear Dynamics in Mechatronic Applications

IMPERIO: behavioral change Interventions Made PERsonal, engagIng & lOng-term

Meta Data Enrichment for Improving the Quality and Usability of Botanical Collections

Spatiotemporal Event Detection for Real-Time Multi-Domain Applications

Automatic Detection of Parasites in Stool and Blood Smear Images using Trustworthy Machine Learning

Automatic detection of pulmonary tuberculosis in chest X-ray images using trustworthy machine learning

Digital innovation for man and society

Enabling personalized medicine by optimizing disease treatments with hybrid machine learning

Explainable, human-in-the-loop hybrid AI, resolving conflicting user feedback

Explainable, human-in-the-loop hybrid AI, resolving conflicting user feedback and in a federated learning setting

HEROI2C: Hybrid machinE leaRning for Improved Infection management in Critically ill patients

Hybrid machine learning with BIM for energy optimization and dweller well-being in smart buildings

Monitoring offshore wind turbines using advanced sensor technologies

Motion Analysis & adaptation using wearable MEMS sensors

Physics-enhanced machine learning for domain-aware predictive maintenance.

Promoting stable remission in depression by combining e-health and cognitive science: the development of DEpression’s DIgital foreCAsting Tool (DEDICAT)

Protecting future fusion power plants – Development of efficient and real-time plasma disruption predictors for ITER by combining advanced data-driven models with physics insights

Reliable Uncertainty Quantification for Machine Learning in Healthcare Applications

Time-spatial enrichment of (meta) data for optimizing the exploration and exploitation of scientific collections

Towards precision health by enabling multimodal monitoring in real-life settings using uncertainty based, hierarchical, and time-dynamic models

Towards precision health by enabling multimodal monitoring in real-life settings using uncertainty based hierarchical and time-dynamic models

Trustworthy AI for healthcare

Unobtrusive monitoring of personal chronic disease progression while determining causal relations in real-world settings.

AI-enabling Smart Wound carE Electronics Patches 2 - AI-SWEEP-2

Cyberbullying among adolescents: behavioural determinants and effectiveness of an intervention to promote active positive bystander behaviour

Dynamic hybrid models for virtual scenario testing and optimal design of drivetrains

Testing & optimising a mobile app in Belgium for the prevention and management of COVID-19 infections

Testing & optimising the COVered App for the prevention and management of COVID-19 infections