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sguys99/README.md

Kwang-Myung Yu (유광명)

in-memory-of-mom (2026. 1. 2 /2025. 11. 14 , 2025. 2. 19(49th))

Work experience

  • PwC Consulting, Digital & AI, Director/ Senior ML engineer (2024 ~ 2025)
  • MakinaRocks, AI Project Team, Part leader/ Senior ML engineer (2023 ~ 2024)
  • Samsung Electro-mechanics, Equipment Engineering R&D Institute, Pricipal SW engineer (2020 ~ 2022)
  • Korea Electric Power Corporation(KEPCO), Data science lab., Senior data scientist (2010 ~ 2020)
  • POSCO EnC, Power tech group., Control system engineer (2008 ~ 2010)

Research Interests

  • LLM application : Agent system, Workflow design, RAG, Question Answering, Text-to-SQL
  • Machine learning for industrial application : Anomaly detection(imbalanced learn, unsupervised approach), time series forecasting, process optimization, optimal control
  • MLOps, LLMOps : Model serving, test and evaluation

Honors and Activities

  • Best People awards, PwC Consulting, 2025
  • 2nd prize of the power plant big data AI competition, Korea East-West Power Corporation, 2020
  • Best research award, KEPCO research institute, 2018
  • Academic excellent student, Pusan national university, 2003 ~ 2006
  • Lecture
    • LLM and RAG application, Incheon national university, 2005
    • Data science basics for ICT employees, KEPCO, 2019
    • Control system tuning and data analytics, KITI, 2014 ~ 2023
  • Activities
    • Happy plant : personal blog for Data science, machine learning, and automatic control [link]
    • Turtles : personal AI project [Github]
  • Publications
    • 파이썬 코드로 배우는 Git&Github : [link]
    • git for visual studio users : [link]

Stack








Contact

LinkedIn face book Email

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  1. practice-git-materials practice-git-materials Public

    Python 6 9

  2. research-curator research-curator Public

    Jupyter Notebook

  3. langchain-study langchain-study Public

    Jupyter Notebook

  4. mlops-for-mle mlops-for-mle Public

    Python

  5. ml-project-template ml-project-template Public template

    Python 1

  6. fastapi-study fastapi-study Public

    Python