Koen Helwegen is a PhD candidate at the Dutch Connectome Lab (VU Amsterdam) with eight years of experience bridging deep learning and neuroscience to study cross-disorder brain connectivity. Before academia he helped scale Plumerai from a small research team into a product-focused startup, progressing from algorithm researcher to leading a 6–10 person software team that built efficient inference solutions for resource-constrained devices. He trained rigorously in mathematics and quantitative science (cum laude degrees in mathematics and a multidisciplinary BSc), giving him strong foundations in modeling and statistics applied to neuroimaging. Passionate about climate and sustainable technology, he combines hands-on ML engineering with translational research aimed at understanding disease-related connectivity patterns. An operator who moves comfortably between prototype research and production constraints, he’s equally at home optimizing model architectures as designing experiments to reveal cross-disorder signatures.
8 years of coding experience
3 years of employment as a software developer
Master’s Degree, Mathematics, 8.9/10 (Cum Laude), Master’s Degree, Mathematics, 8.9/10 (Cum Laude) at Utrecht University
VWO (Natuur & Techniek + Natuur & Gezondheid), Exact Sciences, 8.7/10 (Cum Laude), VWO (Natuur & Techniek + Natuur & Gezondheid), Exact Sciences, 8.7/10 (Cum Laude) at KSG De Breul
Bachelor of Science (B.Sc.), Mathematics, Physics, Neuroscience, GPA 3.5/4 (Cum Laude), Bachelor of Science (B.Sc.), Mathematics, Physics, Neuroscience, GPA 3.5/4 (Cum Laude) at University College Utrecht
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