Daye Lim

543 total citations
28 papers, 356 citations indexed

About

Daye Lim is a scholar working on Astronomy and Astrophysics, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Daye Lim has authored 28 papers receiving a total of 356 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Astronomy and Astrophysics, 11 papers in Artificial Intelligence and 3 papers in Molecular Biology. Recurrent topics in Daye Lim's work include Solar and Space Plasma Dynamics (25 papers), Ionosphere and magnetosphere dynamics (12 papers) and Solar Radiation and Photovoltaics (11 papers). Daye Lim is often cited by papers focused on Solar and Space Plasma Dynamics (25 papers), Ionosphere and magnetosphere dynamics (12 papers) and Solar Radiation and Photovoltaics (11 papers). Daye Lim collaborates with scholars based in South Korea, United Kingdom and Belgium. Daye Lim's co-authors include Yong‐Jae Moon, Eunsu Park, Harim Lee, Gyungin Shin, Il‐Hyun Cho, Tae Young Kim, Myungjin Choi, Jin‐Yi Lee, Kyung‐Suk Cho and Tom Van Doorsselaere and has published in prestigious journals such as The Astrophysical Journal, The Astrophysical Journal Supplement Series and Astronomy and Astrophysics.

In The Last Decade

Daye Lim

24 papers receiving 297 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daye Lim South Korea 10 306 164 56 48 30 28 356
Eunsu Park South Korea 11 339 1.1× 193 1.2× 71 1.3× 71 1.5× 31 1.0× 26 424
Yongyuan Xiang China 15 614 2.0× 85 0.5× 31 0.6× 108 2.3× 18 0.6× 33 662
Tatiana Podladchikova Russia 13 422 1.4× 97 0.6× 18 0.3× 89 1.9× 16 0.5× 50 483
Huadong Chen China 16 722 2.4× 90 0.5× 22 0.4× 96 2.0× 15 0.5× 38 833
Xianyong Bai China 13 423 1.4× 66 0.4× 14 0.3× 85 1.8× 14 0.5× 73 458
C. Verbeeck Belgium 13 381 1.2× 116 0.7× 21 0.4× 77 1.6× 16 0.5× 36 414
P. N. Bernasconi United States 12 647 2.1× 72 0.4× 22 0.4× 142 3.0× 14 0.5× 45 706
I. Kontogiannis Greece 12 475 1.6× 120 0.7× 18 0.3× 118 2.5× 20 0.7× 33 502
Sung‐Hong Park South Korea 15 543 1.8× 93 0.6× 21 0.4× 167 3.5× 40 1.3× 43 600
Shibu K. Mathew India 13 568 1.9× 206 1.3× 13 0.2× 86 1.8× 9 0.3× 51 613

Countries citing papers authored by Daye Lim

Since Specialization
Citations

This map shows the geographic impact of Daye Lim's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daye Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daye Lim more than expected).

Fields of papers citing papers by Daye Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daye Lim. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daye Lim. The network helps show where Daye Lim may publish in the future.

Co-authorship network of co-authors of Daye Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Daye Lim. A scholar is included among the top collaborators of Daye Lim based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daye Lim. Daye Lim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Nóbrega-Siverio, Daniel, et al.. (2025). Thin coronal jets and plasmoid-mediated reconnection. Astronomy and Astrophysics. 702. A188–A188. 2 indexed citations
2.
Doorsselaere, Tom Van, et al.. (2025). Stationary quasi-periodic pulsations in 20-second cadence TESS flares. Astronomy and Astrophysics. 700. A178–A178. 1 indexed citations
3.
Lim, Daye, Tom Van Doorsselaere, D. Berghmans, et al.. (2025). Quasi-periodic pulsations in extreme-ultraviolet brightenings. Astronomy and Astrophysics. 698. A65–A65. 1 indexed citations
4.
Verbeeck, C., M. Mierla, D. Berghmans, et al.. (2025). Extreme-ultraviolet transient brightenings in the quiet-Sun corona. Astronomy and Astrophysics. 699. A138–A138. 1 indexed citations
5.
Pant, Vaibhav, D. Berghmans, A. N. Zhukov, et al.. (2024). Statistical investigation of decayless oscillations in small-scale coronal loops observed by Solar Orbiter/EUI. Astronomy and Astrophysics. 685. A36–A36. 12 indexed citations
6.
Lim, Daye, et al.. (2024). Characteristics and energy flux distributions of decayless transverse oscillations depending on coronal regions. Astronomy and Astrophysics. 689. A16–A16. 4 indexed citations
7.
Lim, Daye, et al.. (2024). Undersampling effects on observed periods of coronal oscillations. Astronomy and Astrophysics. 690. L8–L8. 1 indexed citations
8.
Park, Eunsu, Harim Lee, Yong‐Jae Moon, et al.. (2023). Pixel-to-pixel Translation of Solar Extreme-ultraviolet Images for DEMs by Fully Connected Networks. The Astrophysical Journal Supplement Series. 264(2). 33–33. 2 indexed citations
9.
Shanmugaraju, A., et al.. (2022). Active region and flare ribbon properties associated with X-class flares and CMEs of solar cycle 24. Astrophysics and Space Science. 367(3). 2 indexed citations
10.
Moon, Yong‐Jae, et al.. (2021). Visual Explanation of a Deep Learning Solar Flare Forecast Model and Its Relationship to Physical Parameters. The Astrophysical Journal. 910(1). 8–8. 24 indexed citations
11.
Lim, Daye, Yong‐Jae Moon, Eunsu Park, & Jin‐Yi Lee. (2021). Selection of Three (Extreme)Ultraviolet Channels for Solar Satellite Missions by Deep Learning. The Astrophysical Journal Letters. 915(2). L31–L31. 8 indexed citations
12.
Park, Eunsu, Yong‐Jae Moon, Daye Lim, & Harim Lee. (2020). De-noising SDO/HMI Solar Magnetograms by Image Translation Method Based on Deep Learning. The Astrophysical Journal Letters. 891(1). L4–L4. 12 indexed citations
13.
Moon, Yong‐Jae, et al.. (2020). Super-resolution of SDO/HMI Magnetograms Using Novel Deep Learning Methods. The Astrophysical Journal Letters. 897(2). L32–L32. 20 indexed citations
14.
Lim, Daye, et al.. (2020). Higher Radial Harmonics of Sausage Oscillations in Coronal Loops. The Astrophysical Journal. 893(1). 62–62. 4 indexed citations
15.
Kim, Tae Young, Eunsu Park, Harim Lee, et al.. (2019). Solar farside magnetograms from deep learning analysis of STEREO/EUVI data. Nature Astronomy. 3(5). 397–400. 75 indexed citations
16.
Park, Eunsu, Yong‐Jae Moon, Jin‐Yi Lee, et al.. (2019). Generation of Solar UV and EUV Images from SDO/HMI Magnetograms by Deep Learning. The Astrophysical Journal Letters. 884(1). L23–L23. 33 indexed citations
17.
Lim, Daye, Yong‐Jae Moon, Eunsu Park, et al.. (2019). Ensemble Forecasting of Major Solar Flares with Short-, Mid-, and Long-term Active Region Properties. The Astrophysical Journal. 885(1). 35–35. 8 indexed citations
18.
Park, Eunsu, et al.. (2018). Application of the Deep Convolutional Neural Network to the Forecast of Solar Flare Occurrence Using Full-disk Solar Magnetograms. The Astrophysical Journal. 869(2). 91–91. 68 indexed citations
19.
Lee, SangYun, et al.. (2013). Loss cone‐driven cyclotron maser instability. Journal of Geophysical Research Space Physics. 118(11). 7036–7044. 19 indexed citations
20.
Vaz, Frédéric M., et al.. (2006). Optical quality of the nasendoscope with and without the endosheath. The Journal of Laryngology & Otology. 120(5). 385–388. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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