Chris Kitching is a founder and seasoned software engineer with 12 years of experience building tooling and backend systems from research labs to startups. Based in Dordrecht, Netherlands, he founded Spectral Compute in 2017 after engineering and research roles at Sighthound and the University of Cambridge, and internships at Mozilla working on Firefox for Android. He contributes to notable open-source projects such as ROCm/hip, where his work on hipify-clang improved CUDA-to-HIP portability and kernel transformation reliability, and to FAForever, refining Lua backend code to enhance game lobby UX and performance. Comfortable moving between low-level tooling, code porting, and product-facing backend work, he combines academic rigor with startup pragmatism. Peers describe him as a pragmatic engineer who focuses on maintainability and cross-platform compatibility—traits reflected in his repository refactors and test-driven improvements.
12 years of coding experience
4 years of employment as a software developer
MA, Computer Science, 2.i, MA, Computer Science, 2.i at University of Cambridge
Contributions:3 reviews, 769 commits, 165 PRs in 3 years 6 months
Contributions summary:Chris primarily focused on modifying the Lua code for the FAF project, specifically within the context of the game's lobby and user interface. Their contributions included refactoring code related to observer metadata and CPU benchmark results, and also addressing issues around menu navigation and the display of unit information. These changes suggest a focus on improving the user experience and potentially enhancing the performance and accuracy of game data display within the lobby system.
HIP: C++ Heterogeneous-Compute Interface for Portability
Role in this project:
Software Engineer (Focus: Code Porting and Tooling)
Contributions:100 commits, 23 PRs, 1 push in 29 days
Contributions summary:Chris primarily contributed to the `hip` repository, focusing on the `hipify-clang` tool. Their work involved enhancing the tool's functionality by addressing compilation issues, improving macro handling, and refining kernel launch transformations. They also introduced new tests and refactored existing code to improve maintainability and version compatibility. The user's contributions directly impacted the tool's ability to convert CUDA code to HIP, improving its overall utility.
cudaheterogeneousgpuportabilityhip-runtime
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