Introduction

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.

News

• 🌏 Climate Modeling with Neural Advection-Diffusion Equation was accepted in Knowledge and Information Systems (IF=3.205).

• 🅿️ Prediction-based One-shot Dynamic Parking Pricing was accepted in CIKM 2022.

• 🏅 Graph Neural Controlled Differential Equations for Traffic Forecasting was selected for Innovation Awards at Yonsei University.

• 🔝 Graph Neural Controlled Differential Equations for Traffic Forecasting was selected for oral presentation in AAAI 2022. The top 4.21% (380/9,020) of papers were selected for oral presentation in AAAI 2022.

• 🚘 Graph Neural Controlled Differential Equations for Traffic Forecasting was accepted in AAAI 2022.

• 🤔 Linear, or Non-Linear, That is the Question! was accepted in WSDM 2022.

• 🌏 Climate Modeling with Neural Diffusion Equations was accepted in ICDM 2021.

• 🔖 LT-OCF: Learnable-Time ODE-based Collaborative Filtering was accepted in CIKM 2021.

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

• Sep 2020 - Present, Graduate Student Researcher, BigDyL(Big Data Analytics Lab) (Advisor: Prof. Noseong Park)

• Jan 2020 – Sep 2020, Undergraduate Student Researcher, AI & SE Lab (Advisor: Prof. Duksan Ryu)

• Nov 2018 - Dec 2019, Undergraduate Student Researcher, Systems & Software Engineering Lab (Advisor: Prof. Suntae Kim)

Educational Background

• 2020-Present, Integrated Ph.D. Student Dept. of Artificial Intelligence, Yonsei University

• 2016-2020, B. S. Dept. of Software Engineering, Jeonbuk National University

Awards & Scholarships

• 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.

Talks

• Oct 2022, Talk on 1st Workshop on AI held by Yonsei Univ. [Slides][Poster]

• Aug 2022, Poster presentation for AIGS Symposium 2022 held at the COEX Grand Ballroom. [Poster]

• 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]

Service

• Reviewer in Learning on Graph Conference 2022

• Reviewer in IEEE Transactions on Intelligent Transportation Systems 2022

• External reviewer in ICDM 2021, 2022