Yong-Jun Shin

Researcher, ETRI. PhD in software engineering from KAIST.

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I’m a researcher of Electronics and Telecommunications Research Institute (ETRI), a national research institute in South Korea.

I received my Ph.D. in software engineering at Korea Advanced Institute of Science and Technology (KAIST) under the guidance of Professor Doo-Hwan Bae in 2023.

My Ph.D. research focused on data-driven environment model generation for efficient verification of cyber-physical system (CPS) software (e.g., autonomous driving).

My research interests includes

  • simulation-based CPS software (e.g., autonomous driving) validation,
  • environment and uncertainty modeling,
  • self-adaptive systems modeling,
  • statistical verification,
  • model-based software engineering, and
  • meta-modeling

News

Oct 08, 2024 🎤 I was invited to Hannam University and gave a seminar titled “Model-Based Software Engineering Approaches for the Verification of Autonomous Mobility.”
Feb 14, 2024 👋 My new homepage is open!
Feb 05, 2024 🚧 My homepage is under construction.

Latest posts

Highlighted publications

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    Virtual Environment Model Generation for CPS Goal Verification using Imitation Learning
    Yong-Jun Shin ,  Donghwan Shin ,  and  Doo-Hwan Bae
    ACM Trans. Embed. Comput. Syst., Jan 2024
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    Concepts and models of environment of self-adaptive systems: A systematic literature review
    Yong-Jun Shin ,  Joon-Young Bae ,  and  Doo-Hwan Bae
    In 2021 28th Asia-Pacific Software Engineering Conference (APSEC) , Jan 2021
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    Platooning legos: An open physical exemplar for engineering self-adaptive cyber-physical systems-of-systems
    Yong-Jun Shin ,  Lingjun Liu ,  Sangwon Hyun ,  and  Doo-Hwan Bae
    In 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) , Jan 2021
  4. c_12.jpg
    PASTA: An efficient proactive adaptation approach based on statistical model checking for self-adaptive systems
    Yong-Jun Shin ,  Eunho Cho ,  and  Doo-Hwan Bae
    In International Conference on Fundamental Approaches to Software Engineering , Jan 2021