Sam Redmond
Staff Research Scientist at Google DeepMind
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolSam Redmond is a Staff Research Scientist at Google DeepMind and founder of Hedron Vision, with 11 years of experience building applied AI, computer vision, and graphics systems—most notably headset-free holographic displays and a widely used hands-free heart rate app. A Stanford MS in Computer Science and BS in Mathematics, he has a rare combination of deep mathematical rigor (Putnam, USAMO pedigree) and production engineering, shipping tools used across Google/Meta/Microsoft such as a Bazel compile-commands extractor. An experienced educator—Stanford’s youngest CS instructor who created and taught the university’s first Python course—he’s scaled technical curricula to thousands via university courses and a Udacity nanodegree. His background spans systems design, performance engineering, and wireless research at Google X, giving him a strong practical edge in building reliable, high-performance prototypes. Known for mentoring and community work (TreeHacks founder/organizer), Sam quietly blends research curiosity with product delivery and developer tooling expertise.
11 years of coding experience
8 years of employment as a software developer
Menlo SchoolMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Stanford University
English, Spanish
Stackoverflow
460reputation
23kreached
13answers
4questions
Github Skills (17)
tooling10
c-language10
python10
c1110
c1710
bazel10
error-handling10
cpp10
clangd10
cprogramming-language10
clang10
refactoring9
syntax6
css6
java6
Programming languages (8)
Github contributions (5)
hedronvision/bazel-compile-commands-extractor
Sep 2022 - Sep 2022
Goal: Enable awesome tooling for Bazel users of the C language family.
Role in this project:
Backend & Tooling Developer
Backend & Tooling DeveloperContributions:17 commits, 3 branches in 17 days
Contributions summary:Sam primarily contributed to the tooling used for Bazel projects, specifically focused on the `bazel-compile-commands-extractor` repository. Their work included implementing error handling and ensuring the tool's correct invocation with `bazel run`. They refactored code for clarity and efficiency, including simplification of logic using De Morgan's laws. Furthermore, the user made improvements to the project's internal workings, and corrected typos, and provided clearer messaging, improving maintainability and usability.
objective-c-plus-plusobjective-cc-languageclang-tidycpp
stanfordpython/python-assignments
Apr 2016 - Mar 2019
Assignments for CS41
Contributions:89 commits, 72 pushes, 1 branch in 2 years 11 months
pythonmachine-learning
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