As a Computer Vision Engineer, I occupy a unique space. By combining the hands-on, practical foundation of an HBO Bachelor’s with the analytical research depth of a WO Master’s, I bridge the gap between complex theory and real-world execution.
My real strength lies in rapid prototyping. I have a knack for taking abstract concepts and quickly turning them into working software, allowing companies to validate ambitious ideas early without committing massive development resources upfront. Rather than sticking to rigid blueprints, I rely on my technical intuition to find creative, out-of-the-box solutions that actually work.
I thrive in R&D environments tackling ambiguous, unsolved problems at the intersection of:
- Computer Vision & Robotics: Giving machines spatial awareness and intelligence.
- A Hybrid Technical Approach: Utilizing the speed and determinism of classical image processing alongside the power of modern Deep Learning.
I am a natural tinkerer and lifelong learner. In my free time, you’ll usually find me playing around with Linux, hosting self-hosted services on my Raspberry Pis, or calibrating and printing on my 3D printer.
Technical Expertise
- Computer Vision & ML: OpenCV, PyTorch, Scikit-learn
- Data Analysis & Math: NumPy, Pandas
- Robotics: ROS2, Gazebo
- Software Development: Git, CI/CD, Linux
- Programming Languages: Python, C/C++, Rust, Julia
Why I Use What I Use
I’ve been writing code since I was 14. I firmly believe in using the best tool for the job rather than forcing a single language onto every problem:
- Python: My absolute go-to for machine learning, data science, and rapid scripting.
- C++: What I reach for when programming embedded electronics, microcontrollers, and IoT devices (like Arduino and ESP32).
- Julia: My tool of choice for running fast mathematical simulations.
- Rust: The language I love to write when I need modern, memory-safe, and high-performance systems.