Han Guo

I am a PhD student at MIT CSAIL, advised by Prof. Yoon Kim and Prof. Eric P. Xing. Prior to this, I spent several wonderful years at CMU's Language Technologies Institute and the UNC-NLP research group with Prof. Mohit Bansal. These days, I focus primarily on algorithms and systems for scalable and efficient ML/NLP. I am a recipient of 2022 Microsoft Research PhD Fellowship and 2026 Jane Street Graduate Research Fellowship.

Google Scholar  /  CV  /  GitHub

News
  • 2026 Summer Talked about CODA at Jane Street and Moonshot AI.
  • 2026-04 Honored to receive the 2026 Jane Street Graduate Research Fellowship.
  • 2025-06 Started internship with Tri Dao at Together AI.
  • 2025-02 Talked about flexible LLM quantization at Meta (Efficiency lecture series).
  • 2024-12 Test-Time Training received 2nd place in ARC Prize (Paper Award).
  • 2024 Summer Talked about low-bit and non-uniform LLM quantization at Salesforce, Amazon (InfOpt Quantization Talk), Fireworks AI, Bloomberg LLM Reading Group, Neural Magic, and Together AI.
  • 2023-05 Selected as one of the Machine Learning and Systems Rising Stars.
  • 2022-10 Honored to receive the 2022 Microsoft Research Ph.D. Fellowship.
  • 2021-06 Started internship with Yoon Kim at MIT-IBM Watson AI Lab.
  • 2020-06 Started internship with Caiming Xiong and Nazneen Rajani at Salesforce Research.
  • 2019-12 Awarded Finalist for the 2020 CRA Outstanding Undergraduate Researcher Award.
  • 2019-08 Had a wonderful summer working with Boyang Li at Baidu Research.
  • 2018-12 Awarded Honorable Mention for the 2019 CRA Outstanding Undergraduate Researcher Award.
  • 2018-06 Our paper "Dynamic Multi-Level Multi-Task Learning for Sentence Simplification" is selected as Area Chair Favorites at COLING 2018.
  • 2018-05 Thanks NSF / ACL Walker Fund for travel award.
  • 2017-11 Thanks UNC Office of Undergraduate Research for travel award.
Research

This guy makes a nice webpage.