Vasyl Yurchyshyn

4.8k total citations
141 papers, 3.3k citations indexed

About

Vasyl Yurchyshyn is a scholar working on Astronomy and Astrophysics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Vasyl Yurchyshyn has authored 141 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 138 papers in Astronomy and Astrophysics, 31 papers in Molecular Biology and 21 papers in Artificial Intelligence. Recurrent topics in Vasyl Yurchyshyn's work include Solar and Space Plasma Dynamics (136 papers), Stellar, planetary, and galactic studies (75 papers) and Ionosphere and magnetosphere dynamics (59 papers). Vasyl Yurchyshyn is often cited by papers focused on Solar and Space Plasma Dynamics (136 papers), Stellar, planetary, and galactic studies (75 papers) and Ionosphere and magnetosphere dynamics (59 papers). Vasyl Yurchyshyn collaborates with scholars based in United States, South Korea and Ukraine. Vasyl Yurchyshyn's co-authors include V. I. Abramenko, Haimin Wang, Philip R. Goode, Jiong Qiu, Qiang Hu, Ju Jing, T. J. Spirock, Timothy Howard, Wenda Cao and Guo Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and The Astrophysical Journal.

In The Last Decade

Vasyl Yurchyshyn

136 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vasyl Yurchyshyn United States 32 3.2k 881 453 169 109 141 3.3k
Thomas Berger United States 36 3.4k 1.1× 841 1.0× 409 0.9× 95 0.6× 71 0.7× 94 3.6k
C. N. Arge United States 31 3.5k 1.1× 1.3k 1.4× 411 0.9× 194 1.1× 306 2.8× 103 3.6k
A. Hanslmeier Austria 29 2.7k 0.9× 390 0.4× 290 0.6× 152 0.9× 159 1.5× 175 2.9k
R. Oliver Spain 38 3.6k 1.1× 1.2k 1.3× 214 0.5× 160 0.9× 347 3.2× 145 3.8k
W. D. Pesnell United States 24 3.8k 1.2× 662 0.8× 652 1.4× 480 2.8× 224 2.1× 93 4.0k
Kiyoshi Ichimoto Japan 35 5.0k 1.6× 1.2k 1.3× 718 1.6× 111 0.7× 166 1.5× 225 5.2k
Dibyendu Nandy India 24 1.8k 0.6× 825 0.9× 261 0.6× 78 0.5× 202 1.9× 106 2.1k
E. E. DeLuca United States 41 5.2k 1.6× 1.6k 1.9× 335 0.7× 113 0.7× 119 1.1× 147 5.4k
R. I. Bush United States 14 3.8k 1.2× 1.0k 1.1× 732 1.6× 92 0.5× 212 1.9× 27 3.9k
R. S. Bogart United States 20 3.0k 0.9× 964 1.1× 511 1.1× 71 0.4× 263 2.4× 68 3.1k

Countries citing papers authored by Vasyl Yurchyshyn

Since Specialization
Citations

This map shows the geographic impact of Vasyl Yurchyshyn'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 Vasyl Yurchyshyn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vasyl Yurchyshyn more than expected).

Fields of papers citing papers by Vasyl Yurchyshyn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vasyl Yurchyshyn. 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 Vasyl Yurchyshyn. The network helps show where Vasyl Yurchyshyn may publish in the future.

Co-authorship network of co-authors of Vasyl Yurchyshyn

This figure shows the co-authorship network connecting the top 25 collaborators of Vasyl Yurchyshyn. A scholar is included among the top collaborators of Vasyl Yurchyshyn 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 Vasyl Yurchyshyn. Vasyl Yurchyshyn 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.
Samanta, Tanmoy, Alphonse C. Sterling, Yajie Chen, et al.. (2025). Unveiling the Dynamics and Genesis of Small-scale Fine-structure Loops in the Lower Solar Atmosphere. The Astrophysical Journal. 983(2). 144–144. 1 indexed citations
2.
Cao, Wenda, D. E. Jennings, Jiong Qiu, et al.. (2025). High-resolution Observations of an X6.4 Solar Flare in the Mid-infrared. The Astrophysical Journal Letters. 988(2). L56–L56.
3.
Lim, Eun‐Kyung, Jongchul Chae, Kyuhyoun Cho, et al.. (2025). Temporal Evolution of a Network Jet’s Physical Properties Inferred from FISS/GST and IRIS Observations. The Astrophysical Journal. 981(2). 185–185. 1 indexed citations
4.
Zhang, Hongyang, et al.. (2025). Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model. The Astrophysical Journal. 981(1). 37–37.
5.
Samanta, Tanmoy, et al.. (2025). Formation of Chromospheric Fan-shaped Jets through Magnetic Reconnection. The Astrophysical Journal Letters. 985(2). L47–L47.
6.
Wang, Jason T. L., et al.. (2024). Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification. Space Weather. 22(2). 1 indexed citations
7.
Cho, Kyung‐Suk, Pankaj Kumar, Il‐Hyun Cho, et al.. (2023). High-resolution Observations of Plume Footpoints in a Solar Coronal Hole. The Astrophysical Journal. 953(1). 69–69. 3 indexed citations
8.
Yurchyshyn, Vasyl, et al.. (2023). Evolution of coronal magnetic field parameters during X5.4 solar flare. Frontiers in Astronomy and Space Sciences. 10. 1 indexed citations
9.
Wang, Jason T. L., et al.. (2023). Estimating Coronal Mass Ejection Mass and Kinetic Energy by Fusion of Multiple Deep-learning Models. The Astrophysical Journal Letters. 958(2). L34–L34. 3 indexed citations
10.
Lozitsky, V. G., Vasyl Yurchyshyn, Kwangsu Ahn, & Haimin Wang. (2022). Observations of Extremely Strong Magnetic Fields in Active Region NOAA 12673 Using GST Magnetic Field Measurement. The Astrophysical Journal. 928(1). 41–41. 7 indexed citations
11.
Lee, Jeongwoo, et al.. (2022). Solar Chromospheric Network as a Source for Solar Wind Switchbacks. The Astrophysical Journal Letters. 935(2). L27–L27. 7 indexed citations
12.
Joshi, Bhuwan, et al.. (2020). Hard X-Ray Emission from an Activated Flux Rope and Subsequent Evolution of an Eruptive Long-duration Solar Flare. The Astrophysical Journal. 897(2). 157–157. 15 indexed citations
13.
Lim, Eun‐Kyung, Heesu Yang, Vasyl Yurchyshyn, et al.. (2020). Detection of Opposite Magnetic Polarity in a Light Bridge: Its Emergence and Cancellation in Association with LB Fan-shaped Jets. The Astrophysical Journal. 904(2). 84–84. 8 indexed citations
14.
Yang, Heesu, Eun‐Kyung Lim, Vasyl Yurchyshyn, et al.. (2019). Vortex Formations and Its Associated Surges in a Sunspot Light Bridge. The Astrophysical Journal. 882(2). 175–175. 9 indexed citations
15.
Wang, Haimin, Vasyl Yurchyshyn, Chang Liu, et al.. (2018). Strong Transverse Photosphere Magnetic Fields and Twist in Light Bridge Dividing Delta Sunspot of Active Region 12673. Research Notes of the AAS. 2(1). 8–8. 30 indexed citations
16.
Chae, Jongchul, Jeongwoo Lee, Kyuhyoun Cho, et al.. (2017). Photospheric Origin of Three-minute Oscillations in a Sunspot. The Astrophysical Journal. 836(1). 18–18. 32 indexed citations
17.
Song, Donguk, Jongchul Chae, Vasyl Yurchyshyn, et al.. (2017). Chromospheric Plasma Ejections in a Light Bridge of a Sunspot. The Astrophysical Journal. 835(2). 240–240. 11 indexed citations
18.
Yang, Heesu, Jongchul Chae, Eun‐Kyung Lim, et al.. (2016). FINE-SCALE PHOTOSPHERIC CONNECTIONS OF ELLERMAN BOMBS. The Astrophysical Journal. 829(2). 100–100. 10 indexed citations
19.
Song, Hongqiang, et al.. (2005). Towards Real-Time Automated Prediction of Geo-Magnetic Storms Based on Observations of Source Regions of Halo CMEs. AGUSM. 2005. 2 indexed citations
20.
Sorriso‐Valvo, L., V. I. Abramenko, V. Carbone, et al.. (2003). Cancellations analysis of photospheric magnetic structures and flares. Memorie della Societa Astronomica Italiana. 74. 425–429. 3 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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