About
I am currently an AI researcher at TelePIX (Alternative military service: Technical research personnel). I completed my M.S. degree at Yonsei University (Department of Artificial Intelligence), advised by Prof.Noseong Park (now at KAIST). My primary research areas lie in scientific machine learning (SciML), physics-based modeling, with a focus on implicit neural representations and neural operators for high-dimensional scientific data. I also work on operator-based foundation models and AI systems for Earth observation and satellite applications. Broadly, I aim to develop numerically grounded and mathematically interpretable simulation and PDE-consistent learning frameworks that integrate numerical analysis with modern SciML.
I greatly enjoy collaborating with researchers who share similar interests. If you are interested in my research areas or would like to collaborate, please feel free to contact me!(woojin.py@gmail.com)
Publication
Basis-Oriented Low-rank Transfer for Few-Shot and Test-Time Adaptation
J Park, W Cho, J Heo, D Kwon, K Lee
(Under review)
[Paper]
Learning Low Rank Neural Representations of Hyperbolic Wave Dynamics from Data
W Cho, K Lee, N Park, D Rim, G Welper
(Under review)
[Paper]
Sequential Dataset for Satellite Pose Estimation and a Frequency-Space Neural Operator for HIL-Free Generalization Benchmarking
W Cho*, J Park*, S Immanuel, S Chin, J Wang
(Under review)
DRIFT: Dynamics-aware Robust Inference with Latent Filtering for Temporal Satellite Pose Estimation
J Park*, W Cho*, J Park, D Kwon
(Under review)
Meta-learning Structure-Preserving Dynamics
C Jing, U Mudiyanselage, W Cho, M Jo, A Gruber, K Lee
(Under review)
[Paper]
MaD-Scientist: AI-based Scientist solving Parabolic PDEs using Massive Prior Data
M Kang, D Lee, W Cho, J Park, K Lee, A Gruber, Y Hong, N Park
(Under review)
[Paper]
PDEfuncta: Spectrally-Aware Neural Representation for PDE Solution Modeling
M Jo*, W Cho*, U Mudiyanselage, S Lee, N Park, K Lee
NeurIPS 2025
[Paper]
PIANO: Physics-informed Dual Neural Operator for Precipitation Nowcasting
S Chin, J Park, W Cho
NeurIPS Workshop 2025
[Paper]
Fourier-Modulated Implicit Neural Representation for Multispectral Satellite Image Compression
W Cho*, S Immanuel*, J Heo, D Kwon
IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2025 (Oral)
[Paper]
FastLRNR and Sparse Physics Informed Backpropagation
W Cho, K Lee, N Park, D Rim, G Welper
Results in Applied Mathematics 2025
[Paper]
Unveiling the Potential of Superexpressive Neural Networks in Implicit Neural Representations
U Mudiyanselage, W Cho, M Jo, N Park, K Lee
ICLR Workshop 2025
[Openreview]
Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model
S Immanuel, W Cho, J Heo, D Kwon
ICLR Workshop 2025(Best Paper)
[Paper]
[Code]
[Project]
Can we pre-train ICL-based SFMs for the zero-shot inference of the 1D CDR problem with noisy data?
M Kang, D Lee, W Cho, K Lee, A Gruber, N Trask, Y Hong, N Park
NeurIPS Workshop 2024
[Paper]
Neural Compression for Multispectral Satellite Images
W Cho*, S Immanuel*, J Heo, D Kwon
NeurIPS Workshop 2024
[Paper]
[Code]
[Project]
Promoting Sparsity In Continuous-Time Models To Learn Delayed Dependence Structures
F Wu, W Cho, D Korotky, S Hong, D Rim, N Park, K Lee
CIKM 2024
[Paper]
Parameterized Physics-informed Neural Networks for Solving Parameterized PDEs
W Cho, M Jo, H Lim, K Lee, D Lee, S Hong, N Park
ICML 2024 (Oral, Top 1.52%)
[Paper]
[Code]
[Presentation]
Extension of Physics-informed Neural Networks to Solving Parameterized PDEs
W Cho, M Jo, H Lim, K Lee, D Lee, S Hong, N Park
ICLR Workshop 2024
[Paper]
[Code]
Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer
Y Yu, J Choi, W Cho, K Lee, N Kim, K Chang, C Woo, I Kim, S Lee, J Yang, S Yoon, N Park
ICLR 2024
[Paper]
[Code]
Education
- Yonsei University (Aug. 2024)
M.S in Artificial Intelligence
- Yonsei University (Aug. 2022)
B.S in Atmospheric science
B.S in Electrical electronic engineering - Sejong Science High School (Feb. 2017)
Career
- Telepix ( Jun. 2024 - Present )
AI research team (Alternative military service)
- Arizona State University ( Jan. 2024 - Jun. 2024 )
Visiting Researcher (hosted by Prof.Kookjin Lee)
Academic Activities
Conference Reviewer
- Conference on Neural Information Processing Systems (NeurIPS)
- International Conference on Machine Learning (ICML)
- International Conference on Learning Representations (ICLR)
- Conference on Computer Vision and Pattern Recognition (CVPR)
ESA-NASA International Workshop on AI Foundation Model for Earth Observation
- A Unified Framework for Multi-resolution and Multi-spectral Satellite Imagery in Foundation Model Training (First author)
- Multi-modal Foundation Model for EO and SAR Images (First author)
Invited Talk
- Physics-informed Machine Learning and the Road to Scientific Foundation Models (hoted by ETRI)
- AI for Computational Science and Space Exploration (hosted by Postech, EFFL)
- Scientific Machine Learning (hosted by KIAS: Korea Institute For Advanced Study)
- Parameterized Physics-informed Neural Networks for Parameterized PDEs (hosted by ML2)
- Latest Trends in Machine Learning based Physics Simulation (hosted by Samsung Electronics)
- Physics-informed Neural Networks for Solving PDEs (hosted by Alsemy)
Scholarship
- ICML Financial Aid: 2024
- Google Conference Scholarship: 2024
- AAAI Scholarship: 2024
- ILJU Academy and Culture Foundation : 2019-2022