Haimin Wang

16.9k total citations · 2 hit papers
370 papers, 11.5k citations indexed

About

Haimin Wang is a scholar working on Astronomy and Astrophysics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Haimin Wang has authored 370 papers receiving a total of 11.5k indexed citations (citations by other indexed papers that have themselves been cited), including 326 papers in Astronomy and Astrophysics, 80 papers in Molecular Biology and 45 papers in Artificial Intelligence. Recurrent topics in Haimin Wang's work include Solar and Space Plasma Dynamics (316 papers), Ionosphere and magnetosphere dynamics (155 papers) and Astro and Planetary Science (143 papers). Haimin Wang is often cited by papers focused on Solar and Space Plasma Dynamics (316 papers), Ionosphere and magnetosphere dynamics (155 papers) and Astro and Planetary Science (143 papers). Haimin Wang collaborates with scholars based in United States, China and South Korea. Haimin Wang's co-authors include Chang Liu, Philip R. Goode, H. Zirin, Ju Jing, Jiong Qiu, Vasyl Yurchyshyn, Jongchul Chae, Yong‐Jae Moon, Yan Xu and C. Denker and has published in prestigious journals such as Nature, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Haimin Wang

346 papers receiving 11.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Sodium taurocholate cotransporting polypeptide is a functional receptor for human hepatitis B and D virus

2012 1.6k citations Guocai Zhong, Wenhui He et al. profile →
Magnetic Reconnection as the Driver of the Solar Wind

2023 85 citations Haimin Wang et al. The Astrophysical Journal profile →

Peers

Haimin Wang

AA

MB

EPIDE

AI

HEPAT

Michael Joyce United States

B. Allen United States

Yutaka Komiyama Japan

Joseph Lehár United States

K. Nomoto Japan

Hiroyuki Nakano Japan

Hiroshi Nakashima Japan

David Parkinson United States

Hiroyuki Tomita Japan

M. Lombardi Italy

Michael Joyce United States

Haimin Wang

2.4k ×0.3

AA

1.0k ×0.4

MB

787 ×0.5

EPIDE

90 ×0.1

AI

46 ×0.0

HEPAT

Citations per year, relative to Haimin Wang Haimin Wang (= 1×) peers Michael Joyce

Countries citing papers authored by Haimin Wang

Since Specialization

Citations

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

Fields of papers citing papers by Haimin Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haimin Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Haimin Wang. A scholar is included among the top collaborators of Haimin Wang 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 Haimin Wang. Haimin Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Chen, Bin, et al.. (2025). Two Phases of Particle Acceleration of a Solar Flare Associated with In Situ Energetic Particles. The Astrophysical Journal. 983(1). 33–33.

2.

Inoue, Satoshi, Takahiro Miyoshi, Keiji Hayashi, et al.. (2025). Acceleration of Solar Eruptions via Enhanced Torus Instability Driven by Small-scale Flux Emergence. The Astrophysical Journal Letters. 988(1). L36–L36.

3.

Jing, Ju, et al.. (2025). Solar Flares Triggered by a Filament Peeling Process Revealed by High-resolution GST Hα Observations. The Astrophysical Journal Letters. 980(1). L4–L4.

4.

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

5.

Jing, Ju, et al.. (2024). Magnetic Eruption from a Three-ribbon Flare. The Astrophysical Journal. 972(1). 110–110.

6.

Wang, Jason T. L., et al.. (2023). Operational prediction of solar flares using a transformer-based framework. Scientific Reports. 13(1). 18 indexed citations

7.

Inoue, Satoshi, Keiji Hayashi, Takahiro Miyoshi, Ju Jing, & Haimin Wang. (2023). A Comparative Study of Solar Active Region 12371 with Data-constrained and Data-driven Magnetohydrodynamic Simulations. The Astrophysical Journal Letters. 944(2). L44–L44. 8 indexed citations

8.

Verma, M., et al.. (2023). High-resolution imaging of solar pores. Astronomy and Astrophysics. 675. A182–A182. 5 indexed citations

9.

Jing, Ju, et al.. (2023). Characterizing 3D Magnetic Structures in Sunspot Light Bridges. The Astrophysical Journal. 952(1). 40–40. 3 indexed citations

10.

Chen, Bin, Sijie Yu, Dale E. Gary, et al.. (2023). The Solar Origin of an In Situ Type III Radio Burst Event. The Astrophysical Journal. 954(1). 32–32. 5 indexed citations

11.

Xu, Yan, et al.. (2023). Extreme Red-wing Enhancements of UV Lines during the 2022 March 30 X1.3 Solar Flare. The Astrophysical Journal. 958(1). 67–67. 3 indexed citations

12.

Inoue, Satoshi, et al.. (2022). A Data-constrained Magnetohydrodynamic Simulation of the X1.0 Solar Flare of 2021 October 28. The Astrophysical Journal. 940(2). 119–119. 9 indexed citations

13.

Lee, Jeongwoo, et al.. (2022). A High-resolution Study of Magnetic Field Evolution and Spicular Activity around the Boundary of a Coronal Hole. The Astrophysical Journal. 924(2). 137–137. 8 indexed citations

14.

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

15.

Ou, Tianling, Wenhui He, Brian D. Quinlan, et al.. (2021). Reprogramming of the heavy-chain CDR3 regions of a human antibody repertoire. Molecular Therapy. 30(1). 184–197. 10 indexed citations

16.

Liu, Chang, et al.. (2020). An Eruptive Circular-ribbon Flare with Extended Remote Brightenings. The Astrophysical Journal. 899(1). 34–34. 19 indexed citations

17.

Liu, Chang, Jeongwoo Lee, & Haimin Wang. (2019). The Eruption of Outer Spine-like Loops Leading to a Double-stage Circular-ribbon Flare. The Astrophysical Journal. 883(1). 47–47. 7 indexed citations

18.

Kocharov, L. G., S. Pohjolainen, M. J. Reiner, et al.. (2018). Spatial Organization of Seven Extreme Solar Energetic Particle Events. The Astrophysical Journal Letters. 862(2). L20–L20. 11 indexed citations

19.

Liu, Rui, et al.. (2017). Thermodynamics of supra-arcade downflows in solar flares. Springer Link (Chiba Institute of Technology). 18 indexed citations

20.

Masson, S., É. Pariat, G. Valori, et al.. (2017). Flux rope, hyperbolic flux tube, and late extreme ultraviolet phases in a non-eruptive circular-ribbon flare. Springer Link (Chiba Institute of Technology). 24 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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