Scott Lundberg
Member Of Technical Staff at Microsoft AI
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolScott Lundberg is a research-driven machine learning engineer and Member of Technical Staff at Microsoft AI with 12 years of experience applying language models and explainable AI to medicine, healthcare, and finance. He holds a PhD in Computer Science from the University of Washington and has held research roles at Google DeepMind and Microsoft, bridging cutting-edge research with production-ready tools. Scott is a key contributor to the influential SHAP project, improving benchmarks and visualizations that help interpret complex models, and has contributed developer and documentation work across deep learning and LLM-control projects. His background spans signal processing, sparse representations, and applied analytics from earlier roles, giving him a strong foundation in both theory and systems. Based in Seattle, he combines academic rigor with pragmatic engineering, often improving usability through clearer tutorials, error reporting, and robust testing. An understated throughline in his career is a consistent focus on making complex models transparent and actionable for domain experts.
12 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of WashingtonMaster's degree Computer Science, Master's degree Computer Science at Colorado State UniversityAssociate of Arts (A.A.), Associate of Arts (A.A.) at Aims Community College
Github Skills (23)
javascript10
python10
scikit10
machine-learning10
deep-learning10
scikit-learn10
julia10
documentation10
data-analysis10
testing9
debug9
maintenance9
debugging9
xgboost9
code-cleanup9
Programming languages (9)
Github contributions (5)
shap/shap
Nov 2016 - Nov 2022
A game theoretic approach to explain the output of any machine learning model.
Role in this project:
Data Scientist
Data ScientistContributions:44 releases, 29 reviews, 1311 commits in 6 years 1 month
Contributions summary:Scott's commits focused on updating and improving the benchmark measures within the shap/shap repository. These changes involved updating benchmark updates by modifying the measures.py file, and also creating new files with improved visualizations and tests. These changes would impact the models that use standardized features.
explaininterpretabilityshapdeep-learningapproach
guidance-ai/guidance
Dec 2022 - Aug 2024
A guidance language for controlling large language models.
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:30 releases, 7 reviews, 106 PRs in 1 year 8 months
Contributions summary:Scott implemented significant changes in the coding and notebooks directories, indicating contributions to both the backend logic and related processes within the guidance repository. Their work involved merging main branches, fixing bugs, and adding tests, with changes to files like _prompt.py and prompt-display.js. They demonstrated proficiency in code cleanup, including adding JS code, which suggests a focus on both code functionality and integration with the frontend components.
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