Henry Leung is a Senior AI Scientist and recent PhD in Astronomy & Astrophysics from the University of Toronto with nine years of experience applying deep learning to large, cross-domain scientific datasets. He builds and publishes well-tested, well-documented multimodal foundation models—leveraging Transformers and denoising diffusion probabilistic models—to analyze multi-terabyte catalogues of tabular, 1D, 2D, and time-series data from billions of stellar objects. His work, presented at NeurIPS and ICML, bridges academic rigor and production-ready engineering, and he maintains open-source code and models for community use. At CIBC he translates cutting-edge ML research into industry solutions, drawing on prior roles in applied development and teaching to communicate complex ideas clearly. Colleagues cite his uncommon combination of large-scale data handling in astronomy and practical software craftsmanship as a key asset.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Astronomy and Astrophysics, Doctor of Philosophy - PhD, Astronomy and Astrophysics at University of Toronto
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