I am an integrated Ph.D. student advised by Prof. Noseong Park in the Dep. of Artificial Intelligence at Yonsei University. I have a broad interest in graph neural networks, recommender systems, spatio-temporal forecasting, and differential equations. Recently, I have been working on developing graph-based deep learning methods inspired by differential equations in natural science, e.g., diffusion equations.

I was an undergrad at Jeonbuk National University (2016-2020), majoring in Software Engineering. I was privileged to be advised by Prof. Suntae Kim and Prof. Duksan Ryu.


Research Interests

  • Artificial Intelligence

    • Graph Neural Networks

    • Recommender Systems

    • Spatiotemporal Forecasting

    • Neural ODEs/CDEs/RDEs

  • Software Engineering

    • Software Defect Prediction

    • SE for AI & AI for SE

Research Experience

Educational Background


  • Jul 2022, Innovation Award, Yonsei University (Best paper in Dept. of Artificial Intelligence) [link]

    • 대학원 혁신 우수 논문상 (학과우수상)

  • Feb 2021, Best Paper Awards, the 23rd Korea Conference on Software Engineering (KCSE 2021)

  • Jun 2019, Best Paper Awards, Korean Institute of Information Technology

  • 2018, The National Scholarship for Science and Engineering, KOSAF(Korea Student Aid Foundation)

    • This scholarship supports undergraduates with strong academic performance in science and engineering, with the purpose of developing future leaders in those fields.


  • Jul 2022, Invited talk on Top-conference session, Korea Computer Congress (KCC 2022) [Slides]

  • Nov 2021, Graph-based Collaborative Filtering and Neural ODEs, 한국인공지능학회(KAIA) | LG AI Research, (This talk is part of a tutorial called "Deep Learning Inspired by Differential Equation". ) [Slides]


  • Reviewer in IEEE Transactions on Intelligent Transportation Systems

  • External reviewer in ICDM 2021, 2022