Jeongwhan Choi (최정환)
Jeongwhan Choi is a Ph.D. candidate advised by Prof. Noseong Park in the Dep. of Artificial Intelligence at Yonsei University. His research interests span a variety of areas including graph neural networks, recommender systems, spatio-temporal forecasting, and differential equations. Recently, his focus has been on the development of graph-based deep learning methods inspired by differential equations in natural science, such as heat diffusion equations.
Previously, he completed his undergraduate studies at Jeonbuk National University (2016-2020), where he majored in Software Engineering. During this time, he had the opportunity to be mentored by Prof. Suntae Kim and Prof. Duksan Ryu.
My Erdős number is 4: Noseong Park → Sushil Jajodia → Yechezkel Zalcstein → Paul Erdős.
📈 Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations was accepted in IEEE International Conference on Big Data (Big Data 2023).
🕸️ QoS-Aware Graph Contrastive Learning for Web Service Recommendation was accepted in APSEC 2023.
📨 Blurring-Sharpening Process Models for Collaborative Filtering was invited to the "Top Conference Session" at KCC 2023.
🌏 Climate Modeling with Neural Advection-Diffusion Equation was accepted in Knowledge and Information Systems (IF=2.531).
🅿️ 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 invited to the "Top Conference Session" at KCC 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.
Selected Publications (see all)
Jeongwhan Choi and Noseong Park, "Graph Neural Rough Differential Equations for Traffic Forecasting", ACM Transactions on Intelligent Systems and Technology (TIST), 2023.
Jeongwhan Choi, Seoyoung Hong, Noseong Park, and Sung-Bae Cho, "GREAD: Graph Reaction-Diffusion Networks," ICML 2023.
Jeongwhan Choi, Seoyoung Hong, Noseong Park, and Sung-Bae Cho, "Blurring-Sharpening Process Models for Collaborative Filtering," SIGIR 2023.
Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, and Noseong Park, "Graph Neural Controlled Differential Equations for Traffic Forecasting," AAAI 2022.
Jeehyun Hwang, Jeongwhan Choi, Hwangyong Choi, Kookjin Lee, Dongeun Lee, and Noseong Park, "Climate Modeling with Neural Diffusion Equations", ICDM 2021.
Jeongwhan Choi, Jinsung Jeon, and Noseong Park, "LT-OCF: Learnable-Time ODE-based Collaborative Filtering", CIKM 2021.
- Artificial Intelligence
Graph Neural Networks
Differential Equations-based Deep Learning
- Software Engineering
Software Analytics & Software Defect Prediction
Awards & Scholarships
Jul 2022, Innovation Award, Yonsei University (Best paper in Dept. of Artificial Intelligence) [link]
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.
Jun 2023, Talk on 1st Seminar held by Graph User Group (GUG).
Jun 2023, Invited talk on Top-conference session, Korea Computer Congress (KCC 2023)
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 IRonGraphs 2024: First International Workshop on Graph-Based Approaches in Information Retrieval, co-located with ECIR 2024
Reviewer in 4th Workshop on Graphs and More Complex Structures for Learning and Reasoning (GCLR) colocated with AAAI 2024
Reviewer in SDM 2024
Reviewer in AAAI 2024
Reviewer in Applied Artificial Intelligence 2023 (2 times)
Reviewer in KDD 2023
Reviewer in Learning on Graph Conference 2022, 2023
Reviewer in IEEE Transactions on Intelligent Transportation Systems 2022
Reviewer in ICDM 2021, 2022