Yong-chan Park
About Me
I am a postdoctoral researcher in Computer Science and Engineering at Seoul National University, advised by Prof. U Kang. I received my Ph.D. in Computer Science Engineering and my B.S. in Mathematical Sciences from Seoul National University. My research interests include time series analysis and tensor analysis.
Contacts
- Tel: +82-2-880-7263
- Email: ycpark6767@gmail.com
- Data Mining Lab.
Computer Science and Engineering
Seoul National University - [ Google Scholar | DBLP | CV ]
Research Interests
- Time series analysis
- Tensor analysis
- Anomaly detection
Awards
- SNU CSE Best Ph.D. Thesis Award, 2026
- KDD 2025 Student Travel Award, 2025
- SNU BK21 Star Student Researcher Fellowship, 2023
Publications
-
Fast and Accurate Online Coupled Matrix-Tensor Factorization via Frequency Regularization
Yong-chan Park, SeungJoo Lee, and U Kang
KDD 2026 [ paper | code ] -
Fast and Accurate Temporal Super-Resolution via Residual-Aware Coupled Tensor Factorization
Nam Kyu Kang, Yong-chan Park, and U Kang
ICASSP 2026 [ paper | code ] -
Offline and Online Coupled Tensor Factorization with Knowledge Graph
SeungJoo Lee, Yong-chan Park, and U Kang
PLOS ONE 2025 [ paper | code ] -
SwaGNER: Leveraging Span-aware Grid Transformers for Accurate Nested Named Entity Recognition
SeungJoo Lee, Yong-chan Park, and U Kang
CIKM 2025 [ paper ] -
PuzzleTensor: A Method-Agnostic Data Transformation for Compact Tensor Factorization
Yong-chan Park, Kisoo Kim, and U Kang
KDD 2025 [ paper | bibtex | code | PPT ] -
Accurate Coupled Tensor Factorization with Knowledge Graph
SeungJoo Lee, Yong-chan Park, and U Kang
BigData 2024 [ paper | code ] -
Accurate Stock Movement Prediction via Multi-Scale and Multi-Domain Modeling
JinGee Kim, Yong-chan Park, Jaemin Hong, and U Kang
BigData 2024 [ paper ] -
Fast and Accurate PARAFAC2 Decomposition for Time Range Queries on Irregular Tensors
Jun-Gi Jang, Yong-chan Park, and U Kang
CIKM 2024 [ paper | bibtex | code ] -
Fast Multidimensional Partial Fourier Transform with Automatic Hyperparameter Selection
Yong-chan Park, Jongjin Kim, and U Kang
KDD 2024 [ paper | bibtex | code | PPT ] -
Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors–Algorithm and Application
Jun-Gi Jang, Jeongyoung Lee, Yong-chan Park, and U Kang
KDD 2023 [ paper | bibtex | code ] -
DAO-CP: Data-Adaptive Online CP Decomposition for Tensor Stream
Yong-chan Park*, Sangjun Son*, Minyong Cho, and U Kang (*equal contribution)
PLOS ONE 2022 [ paper | bibtex | code ] -
Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts
Jaemin Yoo, Yejun Soun, Yong-chan Park, and U Kang
KDD 2021 [ paper | bibtex ] -
Fast and Accurate Partial Fourier Transform for Time Series Data
Yong-chan Park, Jun-Gi Jang, and U Kang
KDD 2021 [ paper | bibtex | code ]
Professional Services
- KDD 2026 (Reviewer)
- ICML 2026 (Reviewer)
- AAAI 2026 (Reviewer)
- NeurIPS 2025 (Reviewer)
- KDD 2025 (Reviewer)
- KDD 2024 (Reviewer)
- KDD 2022 (Reviewer)
- NeurIPS 2021 (Reviewer)
Teaching Experiences
Teaching Assistant
- Machine Learning (Dec. 2023 - Jan. 2024) LG Electronics
- Machine Learning (Jul. 2023 - Aug. 2023) Hyundai Motor Company
- Advanced Data Science (Jan. 2023 - Feb. 2023) LG Electronics
- Deep Learning (Mar. 2022 - Jun. 2022) Samsung Electronics
- Deep Learning (Sep. 2021 - Dec. 2021) Samsung Electronics
- Deep Learning (Mar. 2021 - Jun. 2021) Samsung Electronics
- M1522.001400 Introduction to Data Mining (Spring 2021) Seoul National University
- M1522.000900 Data Structure (Fall 2020) Seoul National University