Main Data Scientist in a Start-Up developing smart beehives with eco-friendly pest treatment. Main objective is to use embedded sensor data to determine current state of honeybee brood.Responsibilities involve simulation, data collection and ML modelling.

Machine Learning engineer on an Object Detection system for road damage detection. Worked on dataset improvement and set up a scalable workflow for dataset iteration. Maintained Kubeflow pipelines for training and batch inference, integrations between labeling tools and data platform, ML-related tooling for dataset management, version tracking and customer onboarding. Example: I developed a dataset versioning system based on Dolt. I led a team of three people (including myself) and handled communication with stakeholders.

Applied ML theory and causality to Object Detection. Implemented out-of-distribution learning methods from literature and proposed by myself in BrainCreators’ Detectron2 fork.

Part-time position in a team of three students. We designed and produced a usable prototype battery (690V, 12kWh) for a deep-sea (4 km) application, without a pressure housing. My main responsibilities were the custom design of the electronics and software, and general project management.

Full-time position, leading the electrical design and software development for a Formula Student race car. This longtime high-ranking team has been world champion five times. Our car won FS Netherlands and was highly competitive in two other competitions.I managed a team of 10-15 people, made high-level conceptual choices, and was directly involved in software and hardware development. See video.

Tutored high-school students as preparation for final exams. Ilearned how to teach people by guidance rather than explanation,and developed skills to give effective feedback.