Bart Keulen is a robotics engineer and PhD candidate in machine learning with 11 years of hands-on experience building perception-driven robotic systems and research-grade ML tools. He has delivered production-ready visual guidance and behavior frameworks for autonomous driving robots at Avular, and co-authored peer-reviewed work on deep network regularization while lecturing and supervising students at Universität Innsbruck. His background spans mechanical engineering, systems & control, and software engineering—enabling him to bridge hardware, control theory, and modern deep learning methods. Past entrepreneurial roles show he turns customer needs into shipped products, from web services to laser-cutting logistics, and a research stint that cut RL learning times by up to 95% hints at a talent for algorithmic efficiency. Based in Eindhoven, he thrives in diverse, international teams and balances technical rigor with a practical, outcomes-focused mindset.
11 years of coding experience
7 years of employment as a software developer
PhD Candidate, Machine Learning, PhD Candidate, Machine Learning at Universität Innsbruck
Master's Degree, Systems and Control, Master's Degree, Systems and Control at Delft University of Technology
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