À propos de Michael
I'm a freelance Computer Vision & AI engineer with over 12 years (6 years professional) of hands-on experience architecting and delivering 30+ vision-driven solutions across industrial, medical, and embedded domains. Specialized in hyperspectral imaging, real-time AI pipelines, 3D vision, computer graphics, rendering, synthetic data, and custom hardware integration. I am a former technical lead in AI and computer graphics as well as a very experienced technical interviewer. For more information check synaptivision.com.
Néerlandais
Bilingue ou natif
Anglais
Capacité professionnelle complète
Français
Capacité professionnelle limitée
Accepte de travailler sur site
Tienen (jusqu’à 40 km)
Expériences
- Apixa: Rodent detection in food produceTechnical lead - Computer Vision, AI & Computer GraphicsAGROALIMENTAIREavril 2025 - septembre 2025 (5 mois)Leuven, BelgiqueDesigned and implemented a computer vision system to detect the presence of rodents in produce before packaging. The project combined high-resolution imaging with custom-trained detection models to identify contaminants in real time at high frame-rates. Developed a workflow that integrated with existing bagging lines, using automated inspection to improve food safety, reduce contamination risks, and ensuring operational efficiency.
- Apixa: Salad mix segmentationTechnical lead - Computer Vision, AI & Computer GraphicsAGROALIMENTAIREfévrier 2024 - juin 2025 (1 an et 4 mois)Leuven, BelgiqueDesigned and implemented a segmentation system using synthetic data and hyperspectral imaging to accurately differentiate and classify components in mixed salads. The model enables automated sorting and quality control during the bagging process for grocery stores, improving efficiency and consistency in product packaging.
- Apixa: Indoor Localization and Tracking via RackpolesTechnical lead - Computer Vision, AI & Computer GraphicsLOGISTIQUE & SUPPLY CHAINjanvier 2024 - janvier 2025 (1 an)Leuven, BelgiqueDeveloped a computer vision system to detect rackpoles in warehouse images as a precursor for high-precision indoor localization. Worked with a limited dataset affected by significant encoding artifacts, requiring advanced image processing and robust detection methods to reliably identify rackpoles. The solution improved the accuracy of warehouse localization workflows and provided a foundation for tracking systems, despite challenging visual conditions and data limitations.
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Formations
- Master of Engineering: Computer ScienceKU Leuven2019Specialisation in AI (+took all courses in computer vision and computer graphics.)
- Bachelor in de informaticaKU Leuven2017Minor in business & innovation