Donguk Jung is a software engineer with 11 years of experience bridging low-level systems engineering and machine learning, currently focused on speech recognition and model compression at Skelter Labs in Seoul. He holds dual bachelor’s degrees in Computer Science and Mathematical Sciences from KAIST and combines strong C++ and Python skills with a deep interest in algorithms and ML/DL. At Samsung and Skelter Labs he improved on-device ASR accuracy and compressed transformer models to run on low-spec hardware, while also building robust data pipelines and optimizing decoding performance. His open-source contributions to high-profile runtimes like dotnet/runtime and the Dart SDK highlight expertise in system-level optimizations and compiler backend improvements that reduce memory and startup overhead. Fast-learning and detail-oriented, he pairs practical production experience with academic rigor to tackle performance-critical problems end-to-end. An uncommon strength is his track record of squeezing large models and runtimes into constrained environments without sacrificing accuracy.
.NET is a cross-platform runtime for cloud, mobile, desktop, and IoT apps.
Role in this project:
Back-end Developer
Contributions:423 reviews, 27 commits, 91 PRs in 2 years 8 months
Contributions summary:Donguk contributed to the .NET runtime, specifically focusing on low-level system-level optimizations. Their work includes marking relocation sections as "NotNeeded" to reduce memory footprint, enabling NGEN for aggressively optimized methods to improve startup time, and converting AssemblyNative::Load and AppDomainNative::CreateDynamicAssembly to QCalls to remove libunwind overhead. They also fixed build errors and addressed various platform-specific issues.
The Dart SDK, including the VM, JS and Wasm compilers, analysis, core libraries, and more.
Role in this project:
Back-end Developer
Contributions:5 commits, 3 PRs, 7 comments in 1 month
Contributions summary:Donguk primarily contributed to the Dart SDK's compiler and runtime, focusing on optimization and code generation. Their work involved modifying the ARM backend, specifically updating instructions to use immediate operands for arithmetic operations. Additionally, the user addressed issues related to printing and improving the accuracy of compiler output, such as stack bitmap printing. The commits also included refactoring and code improvements to enhance performance.
dartsdkdart2jscore-librariesflutter
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