Jeongwhan Choi (최정환)
Integrated Ph.D Student
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.
🌏 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 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.
- Artificial Intelligence
Graph Neural Networks
- Software Engineering
Software Defect Prediction
SE for AI & AI for SE
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.
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 Learning on Graph Conference 2022
Reviewer in IEEE Transactions on Intelligent Transportation Systems 2022
External reviewer in ICDM 2021, 2022