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Hao-Jun Michael Shi

Research Scientist

Hao-Jun Michael Shi is a Research Scientist at Meta since August 2021, focusing on scalable and distributed training optimization methods for ranking/recommendation, generative AI, and content understanding applications. Prior to this role, Hao-Jun was a Research Intern at Facebook from January 2019 to May 2019, where the development of the quotient-remainder hashing trick for embedding compression and the investigation of multi-pass training for deep learning-based recommendation systems occurred. Hao-Jun also served as a Research Assistant at Northwestern University from April 2017 to August 2021, conducting research on second-order optimization algorithms and developing the PyTorch-LBFGS module. Educational qualifications include a PhD in Industrial Engineering and Management Sciences from Northwestern University (2021), an MS from the same institution (2017), and a BS in Applied Mathematics from the University of California, Los Angeles (2016).

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San Francisco, United States

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