Tessa Van Der Heiden is a Senior Data Scientist with eight years of industry and academic experience building ML-driven products for automotive and media platforms. She has a strong systems-and-control foundation (MSc, Delft) and a track record at BMW of turning research—GAN-DDPG trajectory prediction, planning for human-robot interaction—into published, deployable solutions. More recently she helped the Dutch public broadcaster scale personalized recommendations for 3 million weekly users and improved resilient search handling of spelling and syntax errors. Tessa bridges deep research (inverse reinforcement learning for image-based autonomous driving) with production engineering, shipping features in cross-functional teams and on real hardware. Colleagues describe her as pragmatic and safety-minded: she has repeatedly prioritized safe exploration and robustness over optimistic prototypes. Based in Utrecht, she blends academic rigor with product focus to deliver interpretable, safety-first ML systems.
8 years of coding experience
6 years of employment as a software developer
Master of Science (MSc) Systems & Control, Master of Science (MSc) Systems & Control at Delft University of Technology
FLORA: Future prediction of obstacle locations in traffic scenes for collision avoidance
Contributions:348 commits, 102 pushes, 1 branch in 3 years 5 months
predictionflorascenescollision-avoidanceavoidance
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