Jeongwhan Choi 최정환
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Jeongwhan Choi, Ph.D. jeongwhan.choi [at] kaist [dot] ac [dot] kr |
About
I am a Post-doctoral Researcher at the Information & Electronics Research Institute, KAIST, working with Noseong Park. I received my Ph.D. in Artificial Intelligence from Yonsei University in August 2025, co-advised by Noseong Park and Sung-Bae Cho. My research focuses on developing principled methods for deep learning on graphs, addressing fundamental challenges such as over-smoothing and over-squashing. I work at the intersection of graph neural networks, differential equations, Transformers, and dynamical systems, with applications spanning recommender systems, spatiotemporal forecasting, and scientific machine learning. My work broadly seeks to advance both the theoretical foundations and practical efficiency of graph learning — from training-free inference methods to physics-inspired architectures. My most influential work, STG-NCDE (AAAI 2022), introduced neural controlled differential equations to spatiotemporal graphs and was ranked 13th among the most influential AAAI 2022 papers with nearly 500 citations. My work has appeared at top-tier venues including ICML, NeurIPS, ICLR, AAAI, IJCAI, SIGIR, WSDM, and CIKM, with two oral presentations at AAAI (2022, 2026). I received the Qualcomm Innovation Fellowship (2024) and the Best Paper Runner-up Award from KAIST–Samsung Industry-Academic Collaboration (2025). I was recognized as a Top Reviewer at NeurIPS 2024, LoG 2024, and KDD 2025 (both cycles), and served as Web Chair for CIKM 2025 and Website Chair LoG 2025.
What's New
(Marh 1, 2026) I was invited to serve as General Chair of LoG 2026.
(Jan 26, 2026) “Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors” was accepted in ICLR 2026!
(Nov 19, 2025) I presented “Tackling Over-smoothing and Over-squashing in Deep Learning on Graphs” at the “Making Decisions with AI” seminar, Pusan National University.
(Nov 11, 2025) I received the Best Paper Runner-up Award from KAIST-Samsung Electronics DS Division Industry-Academic Collaboration Program for our paper “Graph Convolutions Enrich the Self-Attention in Transformers!”
(Oct 29, 2025) Our paper “Are Graph Transformers Necessary? Efficient Long-Range Message Passing with Fractal Nodes in MPNNs” has been accepted as an oral presentation at AAAI 2026!
(Sep 19, 2025) TV-Rec: Time-Variant Convolutional Filter for Sequential Recommendation was accepted in NeurIPS 2025!
(Sep 1, 2025) I have joined the Information & Electronics Research Institute at KAIST as a Post-doctoral Researcher.
(what's not new) · All news →
- (Aug 29, 2025) I successfully defended my dissertation and received my Ph.D. in Artificial Intelligence from Yonsei University under the supervision of Prof. Noseong Park and Sung-Bae Cho.
- (July 5, 2025) I am invited as a reviewer for KDD 2026 (first cycle).
- (June 19, 2025) I am invited to be a PC member for WSDM 2026.
- (June 11, 2025) I have been recognized as an [https://kdd2025.kdd.org/research-track-program-committee/\#february_cycle Outstanding Reviewer (Top 10%) for KDD 2025] (February Cycle).
- (May 29, 2025) "Predicting Drug-Drug Interactions: A Deep Learning Approach with GCN-based Collaborative Filtering" was accepted in Artificial Intelligence in Medicine (*IF 6.1*)!
- (May 5, 2025) I will serve as a Website Chair for the Learning on Graph (LoG) conference!
- (Apr 29, 2025) "Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain" was accepted in IJCAI 2025!
- (Apr 8, 2025) I am invited to be a PC member for ECAI 2025.
- (Mar 3, 2025) I am invited to be a Web Chair for CIKM 2025!
- (Mar 2, 2025) [https://www.paperdigest.org/2025/03/most-influential-aaai-papers-2025-03-version/ Paper Digest] announced that "Graph Neural Controlled Differential Equations for Traffic Forecasting" ranked 13th among the most influential papers at AAAI 2022.
- (Feb 27, 2025) As a Ph.D. technical research personnel, I completed a military training program in February!
- (Feb 17, 2025) I am invited to be a reviewer for NeurIPS 2025.
- (Jan 25, 2025) I am invited to be a reviewer for [https://jmlr.org/tmlr/ Transactions on Machine Learning Research (TMLR)].
- (Jan 23, 2025) "PIORF: Physics-Informed Ollivier-Ricci Flow for Long-Range Interactions in Mesh Graph Neural Networks" was accepted in ICLR 2025!
- (Jan 13, 2025) "FraudCenGCL: Enhancing Fraud Detection via Dual-View Graph Contrastive Learning with Account Centrality Features" was accepted for a workshop at AAAI 2025.
- (Jan 8, 2025) I received the "Merit Academic Paper Award" from Yonsei University for PANDA (ICML 2024).
- (Dec 18, 2024) I have been recognized as an Outstanding Reviewer (Top 10%) for KDD 2025 (August Cycle).
- (Dec 3, 2024) I won a 2024 [assets/award/QIFK2024.pdf Qualcomm Innovation Fellowship]!
- (Nov 30, 2024) I was recognized as the "Top Reviewer" from LoG 2024.
- (Nov 5, 2024) I am honored to receive a "Top (8%) Reviewer" award from NeurIPS 2024.
- (Oct 29, 2024) I am honored to receive the [assets/award/KFTC.jpeg First Prize (Paper Track on Business Idea Competition)] by the Korea Financial Telecommunications & Clearnings Institute (금융결제원).
- (Oct 24, 2024) "SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation" was accepted in WSDM 2025.
- (Oct 23, 2024) I was qualified as a Qualcomm Innovation Fellowship Finalist in the field of AI/ML.
- (Oct 12, 2024) "Enhanced Fraud Detection in Bank Transfers via Augmented Account Features" was accepted in ICAIF Workshop on Foundation Models for Time Series: Exploring New Frontiers (FMTS) as an oral presentation!
- (Oct 4, 2024) "Graph-based representation approach for deep learning of OLED devices" was accepted in Advanced Intelligent Systems
- (Sep 26, 2024) "Graph Convolutions Enrich the Self-Attention in Transformers!" was accepted in NeurIPS 2024!
- (Aug 12, 2024) Paper Digest announced that our paper, "Graph Neural Controlled Differential Equations for Traffic Forecasting", ranked 14th among the most influential papers at AAAI 2022.
- (Jul 17, 2024) "Bridging Dynamic Factor Models and Neural Controlled Differential Equations for Nowcasting GDP" was accepted in CIKM 2024!
- (Jul 12, 2024) I was awarded the "Merit Academic Paper Award" by Yonsei University for his research "Blurring-Sharpening Process Models for Collaborative Filtering", which was presented at SIGIR 2023.
- (May 2, 2024) PANDA: Expanded Width-Aware Message Passing Beyond Rewiring was accepted in ICML 2024!
- (Apr 17, 2024) SVD-AE: Simple Autoencoders for Collaborative Filtering was accepted in IJCAI 2024!
- (Jan 15, 2024) I was awarded the “Best Paper Award” by Yonsei University for his research "GREAD: Graph Neural Reaction-Diffusion Networks", which was presented at ICML 2023.
- (Jan 16, 2024) Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer was accepted in ICLR 2024!
- (Dec 9, 2023) An Attentive Inductive Bias for Sequential Recommendation Beyond the Self-Attention was accepted in AAAI 2024!
- (Dec 7, 2023) The preprint of our work, Graph Convolutions Enrich the Self-Attention in Transformers!, is released in arXiv.
- (Nov 24, YYYY) GREAD: Graph Neural Reaction-Diffusion Networks was invited to the "Top Conference Session" at KSC 2023.
- (Oct 27, 2023) 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).
- (Oct 27, 2023) HyperNetwork Approximating Future Parameters for Time Series Forecasting under Temporal Drifts was accepted in [https://sites.google.com/view/distshift2023/home?authuser=0 NeurIPS 2023 Workshop on Distribution Shifts (DistShift)].
- (Sep 1, 2023) Jeongwhan Choi started an alternative military service as a Ph.D. technical research personnel. (Sep. 2023)
- (Aug 23, 2023) QoS-Aware Graph Contrastive Learning for Web Service Recommendation was accepted in [https://conf.researchr.org/home/apsec-2023 APSEC 2023].
- (MMM DD, YYYY) Blurring-Sharpening Process Models for Collaborative Filtering was invited to the "Top Conference Session" at KCC 2023.
- (MMM DD, YYYY) Graph Neural Rough Differential Equations for Traffic Forecasting was accepted in ACM Transactions on Intelligent Systems and Technology (TIST) (IF=10.489).
- (MMM DD, YYYY) Jeongwhan Choi has joined as a contributor to the Graph User Group (GUG) community.
- (MMM DD, YYYY) GREAD was invited for SEA-CROGS, where Sandia National Labs and Pacific Northwest National Labs are collaborating to solve scientific problems with deep learning. Prof. Noseong Park, who is my research advisor, will present the paper on the 27th of June via weekly webinars.
- (MMM DD, YYYY) My research work (LT-OCF) is featured in the "Top 23 Python recommender-system Projects" and "Top 14 collaborative-filtering Open-Source Projects" on LibHunt.
- (MMM DD, YYYY) GREAD: Graph Neural Reaction-Diffusion Networks was accepted in ICML 2023.
- (MMM DD, YYYY) Blurring-Sharpening Process Models for Collaborative Filtering was accepted in SIGIR 2023.
- (MMM DD, YYYY) Climate Modeling with Neural Advection-Diffusion Equation was accepted in Knowledge and Information Systems (IF=2.531).
- (MMM DD, YYYY) Prediction-based One-shot Dynamic Parking Pricing was accepted in CIKM 2022.
- (MMM DD, YYYY) Graph Neural Controlled Differential Equations for Traffic Forecasting was selected for the Innovation Awards at Yonsei University.
- (MMM DD, YYYY) Graph Neural Controlled Differential Equations for Traffic Forecasting was invited to the "Top Conference Session" at KCC 2022.
- (MMM DD, YYYY) 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.
- (MMM DD, YYYY) Graph Neural Controlled Differential Equations for Traffic Forecasting was accepted in AAAI 2022.
- (MMM DD, YYYY) Linear, or Non-Linear, That is the Question! was accepted in WSDM 2022.
- (MMM DD, YYYY) Climate Modeling with Neural Diffusion Equations was accepted in ICDM 2021.
- (MMM DD, YYYY) LT-OCF: Learnable-Time ODE-based Collaborative Filtering was accepted in CIKM 2021.