Woojin

Graduate student @Yonsei university

Author Image

© 2025. All rights reserved.

Woojin Cho

I am currently an AI researcher at TelePIX (Alternative military service: Technical research personnel). I completed my M.S. degree advised by Prof.Noseong Park (Bigdata Analytics Lab) in the Department of Artificial Intelligence at Yonsei University and continue to collaborate closely on research. My primary research areas include scientific machine learning, foundation model, implicit neural representations (INR) and satellite technology. Additionally, I have an interest in deep learning frameworks based on meta-learning, pruning and data compression method. In the future, I aspire to research related to simulation techniques by combining numerical analysis methods with scientific ML technologies (e.g., Physics-informed neural networks, Neural operator, etc.). I have a goal to build an artificial intelligence that can be interpreted mathematically and statistically. 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

MaD-Scientist: AI-based Scientist solving Convection-Diffusion-Reaction Equations Using Massive PINN-Based Prior Data
M Kang, D Lee, W Cho, J Park, K Lee, A Gruber, Y Hong, N Park
(Under review)
[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

FastLRNR and Sparse Physics Informed Backpropagation
W Cho, K Lee, N Park, D Rim, G Welper
Results in Applied Mathematics 2025
[Paper]

Example Image

Unveiling the Potential of Superexpressive Neural Networks in Implicit Neural Representations
U Mudiyanselage, W Cho, M Jo, N Park, K Lee
ICLR 2025 Workshop on Weight Space Learning
[Openreview]

Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model
S Immanuel, W Cho, J Heo, D Kwon
ICLR 2025 Workshop on Machine Learning for Remote Sensing (Oral)
[Paper] [Code] [Project]

Neural Functions for Learning Periodic Signal
W Cho*, M Jo*, K Lee, N Park
ICLR 2025
[Paper]

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 2024 Workshop on Foundation Models for Science
[Paper]

Neural Compression for Multispectral Satellite Images
W Cho*, S Immanuel*, J Heo, D Kwon
NeurIPS 2024 Workshop on Machine Learning and Compression
[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 2024 Workshop on AI4DifferentialEquations in Science
[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]

Operator-learning-inspired Modeling of Neural Ordinary Differential Equations
W Cho*, S Cho*, H Jin, J Jeon, K Lee, S Hong, D Lee, J Choi, N Park
AAAI 2024
[Paper] [Code]

Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
W Cho, K Lee, D Rim, N Park
NeurIPS 2023 (Spotlight, Top 3.06%)
[Paper] [Code]

   

Education

  • Yonsei University

    M.S in Artificial Intelligence

  • Yonsei University

    B.S in Atmospheric science
    B.S in Electrical electronic engineering

  • Sejong Science High School

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

Reviewer or Program Committee Member for Conference

  • Conference on Neural Information Processing Systems (NeurIPS): 2024
  • International Conference on Machine Learning (ICML): 2025

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

  • Scientific Machine Learning (hosted by KIAS)
  • 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