Youngseok Hwang
Graduate Researcher
Seoul, South Korea
Summary
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RockstarYoungseok Hwang is a graduate researcher at Seoul National University's Graduate School of Data Science with 14 years of technical experience focused on graph neural networks, AI4Science, and machine learning. He blends academic research with hands-on engineering—contributing build and automation improvements to high-profile TensorFlow repositories and adding iOS support for TensorFlow Lite task APIs. His background includes applied research internships at KISTI and ETRI, a standout ML bootcamp project (MMExplainer) recognized by Google engineers, and practical teaching and leadership roles from lecturing to serving as a military council chair. Comfortable working across research, production builds, and localization, he brings cross-platform build automation and mobile ML deployment expertise that isn’t obvious from titles alone. Based in Seoul, he pairs rigorous research training with a track record of shipping reproducible tooling and localized software for global open-source projects.
14 years of coding experience
English, Korean
Stackoverflow
3,725reputation
358kreached
41answers
5questions
Github Skills (32)
c-language10
ios10
internationalization10
bash10
lang10
localization10
tensorflow-lite10
anylanguage10
cprogramming-language10
api-design9
mobile-development9
cicd9
machine-learning9
gradlew8
xcode8
Programming languages (12)
Github contributions (5)
tensorflow/tflite-support
Jul 2020 - Apr 2022
TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile / ioT devices.
Role in this project:
ML Engineer
ML EngineerContributions:12 reviews, 15 commits, 19 comments in 1 year 9 months
Contributions summary:Youngseok primarily contributed to the iOS support library for the TensorFlow Lite support project. Their work involved adding C API prefixes to avoid symbol collisions, modifying workspace settings for iOS builds, adding iOS code and build rules for the task API, and adding API prefixes to functions. These changes focused on creating and improving the integration and functionality of the TFLite models on iOS platforms, enabling their use within the task library framework.
iot-devicesmachine-learningtflite-modelstensorflowtflite
tensorflow/examples
Oct 2019 - Sep 2021
TensorFlow examples
Role in this project:Automation Engineer / Build & Release Engineer
Automation Engineer / Build & Release EngineerContributions:11 reviews, 22 commits, 6 PRs in 1 year 11 months
Contributions summary:Youngseok primarily contributed to the automation of build processes and infrastructure for the TensorFlow examples repository. They created and modified build scripts for both Android and iOS examples, ensuring the integration and proper configuration of dependencies. Their work involved adjusting build scripts for cross-platform compatibility, specifically for Linux. They also streamlined build processes by targeting release builds and adding retry logic for dependency installation.
tensorflow
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