Curriculum Vitae

PhD Researcher

IDLab, Ghent University - imec

Research on adaptive sensor fusion for autonomous systems, with focus on precision agriculture. Development of LISA (Light-Invariant Spectral Autoencoder) and OHSLIC algorithm for hyperspectral imaging analysis.

• Published in IEEE IoT Journal, WACV, and Neural Computing and Applications
• Developed illumination-invariant deep learning frameworks
• Created efficient UAV-based phenotype segmentation algorithms

PhD

Ghent University - imec

Computer Science Engineering - AI and Sensor Fusion

• Adaptive Sensor Fusion
• Precision Agriculture
• Hyperspectral Imaging
• Deep Learning

Advanced Master

KU Leuven

Artificial Intelligence

• Deep Learning
• Computer Vision
• Data Science
• Machine Learning

Master of Science

Ghent University

Physics

• Complex Systems
• Statistical Mechanics
• Artificial Intelligence Electives

Bachelor of Science

Ghent University

Physics

• Theoretical Physics
• Mathematics
• Computational Methods

In-Field Mapping of Grape Yield and Quality with Illumination-Invariant Deep Learning

IEEE Internet of Things Journal

Development of the LISA framework for illumination-invariant hyperspectral imaging analysis in precision viticulture. An end-to-end IoT-enabled robotic system for non-destructive, real-time mapping of grape yield and quality.

Computational Fairness in Adaptive Neural Networks

Neural Computing and Applications

A novel investigation into the fairness of adaptive neural networks, analyzing disparities in computational resource allocation across demographic subgroups. Introduces computational resource allocation as a new dimension of AI fairness.

Adaptive Clustering for Efficient Phenotype Segmentation of UAV Hyperspectral Data

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops

Introduction of the OHSLIC algorithm for computationally efficient, real-time phenotype segmentation from hyperspectral imaging data. Enables on-device processing on UAVs.