Hyunik Park
Staff Engineer at 삼성전자
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolHyunik Park is a Staff Engineer in Samsung Foundry with 11 years of experience bridging semiconductor process integration and software-driven ML tooling. He holds a PhD in Chemical and Biological Engineering and has led embedded NVM semiconductor processing while translating deep domain knowledge into practical engineering solutions. Unusually for a process integration specialist, he contributes to open-source ML projects—authoring trainer subplugins for NNStreamer and adding training APIs to TizenFX—bringing model-training capability to edge and device platforms. Based in Seoul, he blends hands-on lab expertise from organic and hybrid material development with software design for ML pipelines and device APIs. Colleagues rely on him for cross-disciplinary solutions that connect material science, process optimization, and deployable machine learning.
11 years of coding experience
3 years of employment as a software developer
Bachelor of Engineering (B.Eng.), Chemical Engineering, Bachelor of Engineering (B.Eng.), Chemical Engineering at 고려대학교
Korean, English
Github Skills (20)
api-design10
net10
machine-learning10
c1110
c1710
asp-net10
tensorflow10
dotnet-core10
neural-network10
csharp10
gstreamer9
tizen9
dotnet9
dotnet-new9
tfx9
Programming languages (6)
Github contributions (5)
nnstreamer/nnstreamer
Nov 2022 - Jan 2023
:twisted_rightwards_arrows: Neural Network (NN) Streamer, Stream Processing Paradigm for Neural Network Apps/Devices.
Role in this project:
ML Engineer
ML EngineerContributions:633 reviews, 8 commits, 77 PRs in 1 month
Contributions summary:Hyunik primarily contributed to the development of a trainer subplugin for the NNStreamer project. Their work involved defining the necessary APIs and data structures for the trainer, including properties, framework information, and callback functions. The commits introduce features for model training, including epoch counts, and the ability to handle tensor data within the trainer's subplugin framework. They modified existing files and created a new header file to support the new subplugin feature, demonstrating their deep involvement in the integration of machine learning functionalities into the project.
arrowscaffe2streamtensorflowtizen
Samsung/TizenFX
Apr 2022 - Oct 2022
C# Device APIs for Tizen
Role in this project:ML Engineer
ML EngineerContributions:36 reviews, 32 commits, 1 PR in 5 months
Contributions summary:Hyunik primarily contributed to the `Tizenfx` repository by adding and modifying code related to machine learning, specifically focusing on the `Tizen.MachineLearning.Train` component. Their work included adding methods to retrieve model summaries, defining new enumeration types related to neural network training, and modifying existing comments for clarity. The user also introduced the foundational classes and interop code for layers, optimizers, and datasets, showcasing a strong understanding of the machine learning training pipeline and API design.
dotnetc-sharpcsharptizenfxdevice-apis
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