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Eunsu Park

Postdoctoral Researcher

Education

Ph.D in Solar Physics/Space Weather

Kyung Hee University
School of Space Research
2016.03. - 2020.02.

MSc in Solar Physics/Space Weather

Kyung Hee University
School of Space Research
2014.03. - 2016.02.

BSc in Astronomy and Space Science

Kyung Hee University
Department of Astronomy and Space Science
2008.03. - 2014.02.

Languages

  • Korean (Native)
  • English (Intermediate)
  • Japanese (Beginner)

Interests

  • Space Weather
  • Machine Learning (Deep Learning)
  • Solar Physics

Career Profile

I am a scientist studying solar physics and space weather. I have been actively applying deep learning to my research area. My goal is to improve our understanding of the Sun and enhance our ability to predict the effects of solar activity on Earth. To achieve this, I am trying to develop deep learning models to process, reprocess, and improve the quality of solar and space weather data.

Experiences

Postroctoral Researcher

2022.06. ~ Present
Sun and Space Weather Research Group / Korea Astronomy and Space Science Institute (KASI)
  • Design and developping space weather data pipeline

Research Doctor

2020.03. ~ 2022.05.
Sun and Space Weather Lab (SSWL) / Kyung Hee University (KHU)
  • Development of solar data processing model based on deep learning
  • Design and build of research environment (HW/SW) for SSWL

Publications

This is a colloection of papers that I have participated as a main author. You can find a full list of my publications HERE

  • Pixel-to-pixel translation of solar EUV images for DEMs by Fully-connected Networks
    • Eunsu Park, H. Lee, Y.-J. Moon, J.-Y. Lee, I.-H. Cho, K.-S. Lee, D. Lim, H.-J. Jeong, and J.-O. Lee
    Astrophysical Journal Supplement Series, 264, 33
  • Reply to: Reliability of AI-generated magnetograms from only EUV images
    • Eunsu Park, H.-J. Jeong, H. Lee, T. Kim, and Y.-J. Moon
    Nature Astronomy, 5, 111
  • Denoising SDO/HMI Solar Magnetograms by Image Translation Method Based on Deep Learning
    • Eunsu Park, Y.-J. Moon, D. Lim, and H. Lee
    Astrophysical Journal Letters, 891, L4
  • Generation of solar UV and EUV images from SDO/HMI magnetograms by deep learning
    • Eunsu Park, Y.-J. Moon, J.-Y. Lee, R.-S. Kim, H. Lee, D. Lee, G. Shin, and T. Kim
    Astrophysical Journal Letters, 884, L23
  • Solar farside magnetograms from deep learning analysis of STEREO/EUVI data
    • T. Kim, Eunsu Park, H. Lee, Y.-J. Moon, S.-H. Bae, D. Lim, S. Jang, L. Kim, I.-H. Cho, M. Choi, and K.-S. Cho
    Nature Astronomy, 3, 397
  • Application of Deep Convolutional Neural Network to the Forecast of Solar Flare Occurrence Using Full-Disk Magnetograms
    • Eunsu Park, Y.-J. Moon, S. Shin, K. Yi, D. Lim, H. Lee, and G. Shin
    Astrophysical Journal, 869, 91
  • Observational test of empirical magnetopause location models using geosynchronous satellite data
    • Eunsu Park, Y.-J. Moon, and K. Lee
    Journal of Geophysical Research, 121, 10994-11006