After obtaining my PhD, I started working as a postdoctoral researcher at Ghent University (KERMIT research group, http://www.kermit.ugent.be). In this role, I pursued further research in the field of uncertainty-aware machine learning, provided guidance to fellow PhD students in their research endeavours, and contributed to the department's teaching tasks. I also served as a member of the editorial board for the Machine Learning journal (https://link.springer.com/journal/10994) and as a Program Committee member for UAI 2024 (the 40th Conference on Uncertainty in Artificial Intelligence).

As a teaching assistant (KERMIT research group, http://www.kermit.ugent.be), I have been actively involved in instructing courses on statistics and machine learning. Additionally, I have provided guidance and support as a tutor and promotor for eight master thesis students. My primary research focus centered on crafting algorithms for uncertainty-aware machine learning, particularly in the domain of classification, with applications in bioscience engineering. The outcomes of my work have been published in esteemed journals and presented at reputable AI/ML conferences with A/A* ratings. I organized the workshop on uncertainty in machine learning 2023 (WUML23) and took charge of coordinating biweekly machine learning seminars within my department. Furthermore, I have contributed to the academic community as a reviewer for several journals such as Engineering Applications of Artificial Intelligence (EAAI), Machine Learning (MACH), and the Journal of Machine Learning Research (JMLR).

As a project lead, I was responsible of managing and guiding the Virginia Tech research team in developing machine learning models for analyzing grain products, in collaboration with the Department for Environment, Food, and Rural Affairs of the Government of the United Kingdom. As a data scientist, I was involved in creating a data-driven dashboard tailored to the specific needs of the World Forest ID team. This dashboard serves as an essential tool in tracing various consumer products. Our work has been published in the prestigious journal Nature plants (https://www.nature.com/articles/s41477-024-01648-5) and played a pivotal role in a recent Belgian investigation into Russian wood-based panel imports (https://www.tijd.be/politiek-economie/belgie/algemeen/illegaal-russisch-hout-onderschept-in-belgie/10530099.html).

During this internship, I was responsible for guiding and supporting a team of engineers for setting up a data analytics pipeline for the classification of textile fabrics by using spectroscopy-based machine learning methods.

During my time as a freelance photographer, I was involved in small events/projects for Rotaract Aalter (http://rotaract-aalter.be/), Clo'sis (http://www.closis.be/) and more.

Maintenance and extension of meeting room utilization web app using the existing DYAMAND application. DYAMAND is an easily adjustable application framework for remote control of networked devices and services.