Pang Koh
Incoming Assistant Professor at University of Washington
United States
Summary
👤
Senior🎓
Top SchoolPang Koh is an Assistant Professor and research scientist with 14 years of experience at the intersection of machine learning, medicine, and education. After early leadership roles at Coursera building university-facing products and operations for millions of learners, Pang completed a PhD at Stanford where he applied deep learning to biomedical problems and now focuses on robust ML for healthcare and AI-driven education. He has held research and engineering roles at Google and AI2, and contributes to influential open benchmarks such as WILDS by preparing real-world medical datasets like Camelyon17 for distribution-shift evaluation. Combining academic rigor with product and operational experience, Pang brings both hands-on data preprocessing and high-level systems thinking to translational ML problems.
14 years of coding experience
7 years of employment as a software developer
BSc, Computer Science, with Honors and Distinction, BSc, Computer Science, with Honors and Distinction at Stanford University
Github Skills (6)
data-preprocessing10
python10
machine-learning9
computer-vision8
pandas8
image-processing8
Programming languages (8)
Github contributions (5)
p-lambda/wilds
Dec 2020 - Nov 2022
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
Role in this project:
Data Scientist
Data ScientistContributions:4 releases, 40 reviews, 260 commits in 1 year 11 months
Contributions summary:Pang's commits focus on preprocessing and generating coordinates for the Camelyon17 dataset, indicating work related to preparing data for a machine learning task. They've adapted code from existing sources, modified file generation scripts, and made changes to include all necessary files for a specific stage. These edits also include edits to ensure specific processing options for different stages, and to process the data to use in later stages of a workflow.
loadersshiftswildmachine-learningmachine-learning-benchmark
yewsiang/ConceptBottleneck
Jun 2020 - Sep 2022
Concept Bottleneck Models, ICML 2020
Contributions:10 commits, 9 pushes, 7 comments in 2 years 3 months
interpretabilityosteoarthritis-initiativedeep-learningicml-2020computer-vision
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