Nader Asadi is an ML researcher and Member of Technical Staff with eight years of experience building and aligning large-scale foundation models, most recently contributing to text-to-video generation and rapid research-to-product roles at Haiper, Leonardo.Ai, and Genmo. He blends academic rigor from Mila and Concordia with hands-on industry practice at Huawei and Borealis AI, focusing on efficient training, parameter-efficient fine-tuning, decentralized learning, and robustness to distribution shifts. Nader has a track record of improving training stability and adaptive regularization for noisy time-series, and has collaborated with teams at Meta AI Research and Toyota Research. Based in Old Toronto, he combines deep research expertise with fast-moving startup execution, often working at the intersection of modular skill recombination and scalable alignment techniques.
8 years of coding experience
4 years of employment as a software developer
Master of Science - MS Machine Learning, Master of Science - MS Machine Learning at Mila - Quebec Artificial Intelligence Institute
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Concordia University
Bachelor's degree IT Engineering, Bachelor's degree IT Engineering at Shahid Bahonar University of Kerman
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