Connelly Barnes
Senior Research Scientist 2 at Adobe
Seattle, Washington, United States
Summary
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Senior🎓
Top SchoolConnelly Barnes is a Senior Research Scientist with 14 years of experience bridging academic graphics research and industrial product development, currently at Adobe in Seattle. He holds a Ph.D. in Computer Science from Princeton and previously led a computer graphics research group as an assistant professor, where he combined fundraising, teaching, and production-quality code. Connelly contributes to high-performance imaging toolchains—evidenced by his work on the widely used Halide project, adding bindings and compilation paths to enable fast, portable data-parallel image processing. His profile blends deep theoretical expertise with practical systems engineering, routinely moving ideas from papers to LLVM-backed implementations. Colleagues can expect a researcher-engineer who values reproducible, well-integrated tooling alongside novel graphics research.
14 years of coding experience
11 years of employment as a software developer
Honors B.S. Mathematics, Honors B.S. Mathematics at Oregon State UniversityDoctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Princeton University
Stackoverflow
21reputation
11kreached
1answer
0questions
Github Skills (10)
halide10
c-language10
cprogramming-language10
ocaml10
image-processing9
compiler-compiler9
compiler9
dsl8
libjpeg6
python6
Programming languages (2)
Github contributions (5)
halide/Halide
Oct 2011 - Oct 2013
a language for fast, portable data-parallel computation
Role in this project:
Back-end Developer
Back-end DeveloperContributions:79 commits in 2 years
Contributions summary:Connelly contributed to the cpp_bindings and apps directories, modifying files related to MLFImage, FImage and schedule_transforms. These changes involve integration of Halide with external tools, including cpp and OCaml bindings, to enable fast, portable data-parallel computation. The modifications appear to be focused on supporting image processing pipelines with a focus on enabling LLVM module generation through the doCompile and doLower calls.
computationhexagonhalideparallelgpu
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