Hyunwoo Kim

AGI Research & Real-Time Systems

KETI (Korea Electronics Technology Institute)

About me

Hi, I'm Hyunwoo Kim — a researcher and engineer passionate about AGI, real-time networked systems, and robotics. I work at KETI where I develop Time-Sensitive Networking (TSN) solutions for automotive and industrial applications.

My research spans from low-level embedded systems to high-level AI architectures. I believe in building practical systems that bridge cutting-edge research with real-world deployment.

Interests

IEEE 802.1 TSN standards for deterministic networking. Working on CBS, TAS, FRER implementations for automotive Ethernet. Developed TSN-Traffic-Tester and various performance analysis tools.
Exploring multimodal AI architectures that can process text, vision, and audio. Currently experimenting with HyperCLOVAX and building optimized inference pipelines for edge deployment.
Building autonomous robots using Jetson platforms. Experience with ROS2, LIDAR navigation, and computer vision. Interested in end-to-end driving systems like openpilot.
Firmware development on ESP32, STM32, and custom hardware. Projects include electronic shelf labels, DOOM running on ESP32, and various sensor integrations.
Building browser-based tools for hardware control using WebSerial, WebRTC, and modern web APIs. Making complex systems accessible through intuitive interfaces.

Travel

I enjoy exploring new places and experiencing different cultures. Here's a visual record of my adventures.

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Projects

TSN-Traffic-Tester ★ 2

Comprehensive TSN performance testing suite for CBS, TAS, and FRER

Python TSN Networking
View on GitHub →
esp32doom7 ★ 2

DOOM running on ESP32 with custom display driver

C++ ESP32 Embedded
View on GitHub →
naver (HyperCLOVAX AGI)

Optimized inference pipeline for HyperCLOVAX multimodal AI

Python AI Transformers
View on GitHub →
jetson_robot

Autonomous robot platform with LIDAR and camera on Jetson

Python ROS2 Robotics
View on GitHub →
microchip-velocitydrive-lan9662

Web-based control interface for LAN9662 TSN switch

JavaScript WebSerial TSN
View on GitHub →
mujoco-web

MuJoCo physics simulation running in the browser

JavaScript WASM Simulation
View on GitHub →
tsn-frer-automotive-redundancy

IEEE 802.1CB FRER implementation for automotive networks

Python TSN Automotive
View on GitHub →
lnn

Liquid Neural Network experiments and implementations

Python ML Neural Networks
View on GitHub →

Let's chat

I love collaborating and connecting with others! Feel free to reach out if you're working on similar areas or have ideas to discuss.