Daniel Severo is a Senior Research Engineer at Meta's Superintelligence Labs (FAIR) with a decade of experience bridging hardware, embedded firmware, and state-of-the-art generative modeling research. He earned a Ph.D. from the University of Toronto and the Vector Institute in 2024 studying generative modeling and information theory, and spent much of his graduate work interning at Meta and Google AI on large-scale pre-training and inference for autoregressive, diffusion, and flow-matching models. Prior roles span machine learning in healthcare and recommendation systems, plus early career embedded systems and signal-processing projects, giving him a rare cross-disciplinary fluency from microcontrollers to multi-GPU model scaling. He publishes and contributes research (including work on compression and perceptual modeling) and brings practical production experience from building ML systems in clinical and e-commerce settings. Notably, his trajectory reflects both deep theoretical chops and hands-on engineering—optimizing compute at inference time as well as training—making him adept at turning research advances into scalable systems.
10 years of coding experience
10 years of employment as a software developer
Bachelor of Science - BS Electrical and Electronics Engineering, Bachelor of Science - BS Electrical and Electronics Engineering at Universidade Federal de Santa Catarina
Doctor of Philosophy - PhD Electrical and Electronics Engineering, Doctor of Philosophy - PhD Electrical and Electronics Engineering at University of Toronto
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