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@TranDangKhoaTechnology
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Trần Đăng Khoa TranDangKhoaTechnology

I'm Tran Dang Khoa, a passionate developer on a mission to bridge the gap between hardware and software, turning creative ideas into real-world solutions.

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Trần Đăng Khoa

Trần Đăng Khoa

Automation · Embedded Systems · PCB Design · Robotics

Electrical engineering student at UNETI, building practical systems across hardware, firmware, automation, and software.

GitHub Email YouTube Facebook

Profile views Based in Vietnam


GitHub overview

GitHub statistics Top languages


About me

I enjoy engineering complete systems rather than isolated pieces:

Schematic & PCB → embedded firmware → communication → application software → testing & documentation

I use GitHub as both a project workspace and an engineering notebook, keeping source code, hardware files, experiments, reports, and reusable tooling together whenever that improves traceability.

Engineering focus

  • Embedded systems: STM32, ESP32, Arduino, FreeRTOS and C/C++ firmware architecture.
  • Hardware and PCB: schematic review, component selection, PCB layout and reusable Altium libraries.
  • Robotics and automation: motor control, communication protocols, timeout protection and recovery logic.
  • Software engineering: Python desktop tools, dashboards and testing applications.
  • AI and computer vision: intelligent classification and workflow automation.

Selected public engineering projects

Selected for technical depth, completeness, documentation quality, and relevance to embedded systems, control, PCB design, robotics, and engineering software.

Embedded systems & control

Motor Control Deck repository CYD 2.8 Inch Mini Tivi repository

STM32 FreeRTOS Multi Task Demo repository Do Line repository

Robotics, hardware & PCB

Robot DHTD18A2HN 2025 repository Altium Library repository

Software & developer tooling

Codex Plugin Bridge repository TranslateDub repository


Technical toolbox


Engineering principles

  • Understand the system: interfaces, constraints, failure modes and actual operating conditions come first.
  • Design for verification: logs, test points, reproducible builds and acceptance criteria reduce guesswork.
  • Prefer safe failure modes: timeouts, validation, recovery paths and conservative assumptions are part of the design.
  • Measure before optimizing: performance work should be based on evidence and documented decisions.

Contact

Email · GitHub · YouTube · Facebook

Build the whole system. Verify every layer. Keep improving.

Hardware · Firmware · Automation · Software

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