Thomas Verelst

Thomas Verelst has diverse work experience in the field of AI, machine learning, and computer vision.

Their most recent position is as a Deep Learning Engineer at Axelera AI, where they currently work.

Before joining Axelera AI, they worked as a PhD Researcher at KU Leuven, where their research focused on dynamic neural networks and efficient deep learning techniques. Thomas gained expertise in human pose estimation, segmentation, classification, and object detection. Thomas also has experience in model compression, quantization, transfer learning, and multi-task learning.

Thomas also had an internship as a Machine Learning Intern at Apple, where they conducted research on multi-label image classification with noisy labels and contributed to a pre-print research paper.

Prior to that, they had an internship as an Internship Test Engineer at Nokia, where they developed testsuites for Nokia's Service Router Operating System. Thomas also had an internship at SEMICON Sp. z o.o. in Warsaw, Poland, where they were responsible for SMT and THT production and developed inspection methods for printed circuit boards and lasers.

In addition, Thomas worked as a Student Consultant at AFC - Academics for Companies, where they conducted a market research project for Protect Insurance Company, investigating the feasibility of a mobile application for insurance companies.

Earlier in their career, Thomas worked as a Web Developer at Metro Webdesign, where they developed a web templating framework using HTML5, PHP, CSS3, Javascript (jQuery), and MySQL.

Throughout their work experience, Thomas has gained proficiency in various tools and technologies such as PyTorch, Numpy, OpenCV, CUDA, MLFlow, Numba, Matplotlib, git, pandas, bash, Visual Studio Code, and PyCharm.

Thomas Verelst began their education in 2007 at Sint-Jan Berchmanscollege Westmalle, where they focused on Latin and Mathematics. Thomas then attended KU Leuven from 2013 to 2016, earning their Bachelor of Science (B.Sc.) degree in Electrical Engineering & Computer Science. Following this, Verelst continued their studies at EPFL (École polytechnique fédérale de Lausanne) in 2016-2017, where they pursued a Master of Science (M.Sc.) degree in Electrical engineering and Information technology. Returning to KU Leuven, Verelst completed their Master of Science (M.Sc.) degree in Electrical Engineering in 2018. Currently, they are pursuing a Doctor of Philosophy (PhD) in Electrical engineering and Information technology at KU Leuven, which is expected to be completed in 2022.