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4 followers · 7 following
  • LIG Nex1
  • Seoul, KR
  • 18:39 (UTC +09:00)
  • LinkedIn in/daeha-yoo

Achievements

Achievement: Pull Sharkx2Achievement: Quickdraw

Achievements

Achievement: Pull Sharkx2Achievement: Quickdraw

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AHEAD94/README.md

👨‍💻 About Me

  • Specialized in developing distributed systems with real-time communication and DDS (Pub/Sub middleware).
  • Interested in advanced programming skills, mobile development, computer vision, and indoor localization.

🛠️ Technical Skills

  • Languages: C/C++
  • Networking: TCP/UDP Communication
  • Middleware: Pub/Sub-based DDS (RTI Connext DDS)
  • Distributed Systems: Development for Multi-SBC Environments and ICD-based Inter-System Communication
  • Software Reliability: Unit Testing, Integration Testing, and Static Analysis

📚 Additional Skills & Interests

  • Mobile Development: Swift iOS, Java Android Studio
  • Databases: Firebase, PostgreSQL
  • Machine Learning: PyTorch, TensorFlow
  • Computer Vision: OpenCV, YOLOv5
  • Indoor Localization: Indoor Positioning System (IPS)

Top Langs

💼 Software Engineer | LIG Nex1 (Feb 6, 2023 – Present)

  • Communication Modules: Developed TCP/UDP messaging and control modules for real-time device communication.
  • DDS Middleware: Implemented Pub/Sub messaging using IDL and optimized QoS for efficient data exchange.
  • Testing & Reliability: Conducted unit/integration testing and static analysis to ensure system stability.
  • Linux Development: Built and optimized software for multi-SBC environments.
  • Documentation: Wrote and maintained SRS, SDD, and other technical documentation.

🎓 Education

  • Ajou University
    Master’s in Computer Science (2023)
    Thesis: Data Structure Design from Electronic Architectural Drawings and Its Application for Vision-based Indoor Localization

    Bachelor's in Architectural Engineering & Software Engineering (Double Major, 2021)

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    This repository provides a method to convert architectural CAD drawings into a graph-based structure representing the building layout, enabling indoor localization using computer vision techniques.

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