PeopleofSuperintelligence

Researcher

Pang Wei Koh

Also known as Pang Koh

Pang Wei Koh is an assistant professor in the Allen School at the University of Washington, where his research covers reliable machine learning systems. He earned Stanford bachelor's and master's degrees in computer science in 2013, and he completed his Stanford PhD in 2022. With Percy Liang, he received the ICML 2017 Best Paper Award for work on influence functions, which trace a model's predictions back to its training data. He co-authored the WILDS benchmark of in-the-wild distribution shifts, which appeared on arXiv in December 2020, and he became a 2024 AI2050 Early Career Fellow. He is also among the authors of Olmo 3, a family of fully open language models, and he is a visiting research scientist at the Allen Institute for AI (Ai2).

Works
110
Citations
9,056
h-index
28

Publication numbers from OpenAlex, as of 15 October 2026.

Timeline

  1. 2013

    Stanford degrees and Coursera

    He completes Stanford bachelor's and master's degrees in computer science in 2013. Before his PhD, he works as Coursera's third employee and director of partnerships.

  2. 2017

    An ICML best paper

    He and Percy Liang win the ICML 2017 Best Paper Award for Understanding Black-box Predictions via Influence Functions. The paper uses influence functions to trace a model's prediction back to its training data.

  3. December 2020

    Co-authoring the WILDS benchmark

    He co-authors WILDS, a benchmark of in-the-wild distribution shifts, which appears on arXiv in December 2020.

  4. 2024

    An AI2050 fellowship

    He is named a 2024 AI2050 Early Career Fellow while on the University of Washington faculty.

  5. December 2025

    A coauthor of Olmo 3

    He is among the authors of Olmo 3, a family of fully open language models at 7B and 32B scales, which appears on arXiv in December 2025.

  6. As of October 2026

    Assistant professor at UW

    He is an assistant professor in the Allen School at the University of Washington, after completing his Stanford PhD in 2022. He is also a visiting research scientist at the Allen Institute for AI (Ai2) and a Singapore AI Visiting Professor. His research covers the theory and practice of building reliable machine learning systems.

Sources and credits

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  1. Pang Wei Koh, Assistant Professor - Paul G. Allen School of Computer Science & Engineering cs.washington.edu. Checked 15 October 2026.
  2. Pang Wei Koh | UW College of Engineering engr.washington.edu. Checked 15 October 2026.
  3. ICML 2017 Awards icml.cc. Checked 15 October 2026.
  4. [1703.04730] Understanding Black-box Predictions via Influence Functions arxiv.org. Checked 15 October 2026.
  5. [2012.07421] WILDS: A Benchmark of in-the-Wild Distribution Shifts arxiv.org. Checked 15 October 2026.
  6. Pang Wei Koh - AI2050 ai2050.schmidtsciences.org. Checked 15 October 2026.
  7. [2512.13961] Olmo 3 arxiv.org. Checked 15 October 2026.
  8. Pang Wei Koh - Schmidt Sciences schmidtsciences.org. Checked 15 October 2026.