Jason D'eon is a research statistician and PhD candidate in Computer Science at Dalhousie University, affiliated with the Vector Institute, who applies advanced sequence models and representation learning to music generation and prediction. With a strong theoretical foundation—an MMath in Pure Mathematics from Waterloo focused on Riemannian geometry and a BSc in Math & CS—he blends rigorous math with practical ML to build novel creative tools. He brings ten years of experience across research labs and health-sector analytics, now contributing statistical expertise at Nova Scotia Health Authority. Known for high academic achievement (top-of-class GPAs) and interdisciplinary curiosity, he moves fluidly between abstract geometry and hands-on generative modeling. An underappreciated strength is his history of cross-domain research from nanochemistry to graph theory, which informs a broad, systems-level view of ML problems.
10 years of coding experience
Bachelor of Science - BS, Mathematics and Computer Science, 4.29 CGPA (out of 4.30), Bachelor of Science - BS, Mathematics and Computer Science, 4.29 CGPA (out of 4.30) at Saint Mary's University
Doctor of Philosophy - PhD, Computer Science, 4.30 CGPA (out of 4.30), Doctor of Philosophy - PhD, Computer Science, 4.30 CGPA (out of 4.30) at Dalhousie University
Master's degree, Pure Mathematics, 92 CGPA (out of 100), Master's degree, Pure Mathematics, 92 CGPA (out of 100) at University of Waterloo
Contributions:5 pushes, 1 branch in 1 year 8 months
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