hi, i'm nathan ng

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I'm a postdoctoral research at NYU working with Kyunghyun Cho. I completed my PhD at the University of Toronto while visiting at MIT advised by Marzyeh Ghassemi.

My general research interest is in developing methods to learn efficient and robust representations of discrete-valued sequence data (specifically natural language). I’m also interested in understanding and finding ways to fix their pathologies once trained. My research broadly covers topics in representation learning, interpretability, and out-of-domain robustness/generalization.

Previously I have spent summers interning at Prescient Design with Kyunghyun Cho, Meta with Naman Goyal, and Google with Narendran Thangarajan. I also spent a year working at Facebook AI Research advised by Michael Auli. I completed my undegraduate degree in Computer Science with minors in Mathematics and Music at UCSD in 2018 advised by Julian McAuley and Zachary Lipton.

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