Courses Taught and Guided Master Theses

I was a Teaching Assistant or contributed to the teaching material for the following courses:

• Mathematics of data: from theory to computation (EPFL, course description)

• Data Mining and Neural Networks (KUL, course description)

• Support Vector Machines: Methods and Applications (KUL, course description)

I (co-)supervised the following master students:

• Convolution-based selective state space models for graph signal processing, by Aidan Li (Summer 2024 internship).

• Membership Inference Attacks against Large Vision-Language Models, thesis by Zhan Li for MSc in Computer Science (AY 2024-2025).

• Multiway spectral clustering with Stiefel-Restricted kernel machines, thesis by Edward Vandercruysse for MsC in Mathematical Engineering (AY 2021-2022).

• A non-local similarity framework for the denoising of textured meshes, thesis by Guillaume Roy for MsC in Statistics and Data Science (AY 2020-2021).