Jingjing Shi

421 total citations
20 papers, 283 citations indexed

About

Jingjing Shi is a scholar working on Astronomy and Astrophysics, Instrumentation and Ecology. According to data from OpenAlex, Jingjing Shi has authored 20 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Astronomy and Astrophysics, 13 papers in Instrumentation and 2 papers in Ecology. Recurrent topics in Jingjing Shi's work include Galaxies: Formation, Evolution, Phenomena (16 papers), Astronomy and Astrophysical Research (13 papers) and Astrophysical Phenomena and Observations (4 papers). Jingjing Shi is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (16 papers), Astronomy and Astrophysical Research (13 papers) and Astrophysical Phenomena and Observations (4 papers). Jingjing Shi collaborates with scholars based in China, Japan and United States. Jingjing Shi's co-authors include Ravi K. Sheth, H. J. Mo, Huiyuan Wang, Wentao Luo, Ye Li, Kentaro Nagamine, Hassen M. Yesuf, Bing Zhang, Xuheng Ding and Surhud More and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Astrophysical Journal and Journal of Cleaner Production.

In The Last Decade

Jingjing Shi

20 papers receiving 245 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jingjing Shi China 11 244 125 31 26 20 20 283
Martin Eriksen Spain 11 205 0.8× 83 0.7× 31 1.0× 26 1.0× 5 0.3× 23 243
Carolin Wittmann Germany 8 389 1.6× 244 2.0× 33 1.1× 45 1.7× 6 0.3× 9 405
Pierluigi Cerulo Chile 11 250 1.0× 167 1.3× 14 0.5× 23 0.9× 10 0.5× 21 263
Ryan Keenan United States 7 237 1.0× 85 0.7× 60 1.9× 4 0.2× 9 0.5× 12 318
Todd Small United States 8 421 1.7× 242 1.9× 29 0.9× 19 0.7× 4 0.2× 18 449
Dominik Steinhauser Austria 7 334 1.4× 141 1.1× 42 1.4× 6 0.2× 26 1.3× 10 394
Steve Hatton France 8 377 1.5× 201 1.6× 60 1.9× 27 1.0× 6 0.3× 12 397
M. Soares-Santos United States 9 288 1.2× 126 1.0× 55 1.8× 39 1.5× 3 0.1× 26 298
A. E. Watkins United Kingdom 13 341 1.4× 186 1.5× 14 0.5× 14 0.5× 5 0.3× 30 351
S. Haan Australia 9 281 1.2× 82 0.7× 30 1.0× 9 0.3× 8 0.4× 21 314

Countries citing papers authored by Jingjing Shi

Since Specialization
Citations

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

Fields of papers citing papers by Jingjing Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jingjing Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Jingjing Shi. A scholar is included among the top collaborators of Jingjing Shi 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 Jingjing Shi. Jingjing Shi 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.
Shi, Yao, Huiquan Li, Weiping Liu, et al.. (2024). Multi-objective optimization of clean utilization for zinc leaching residues by rotary kiln using neural network coupled modeling. Journal of Cleaner Production. 470. 143287–143287. 4 indexed citations
2.
Shi, Jingjing, Tomomi Sunayama, Masahiro Takada, et al.. (2024). The intrinsic alignment of galaxy clusters and impact of projection effects. Monthly Notices of the Royal Astronomical Society. 528(2). 1487–1499. 3 indexed citations
3.
Lamman, C, et al.. (2024). The IA Guide: A Breakdown of Intrinsic Alignment Formalisms. SHILAP Revista de lepidopterología. 7. 18 indexed citations
4.
Sunayama, Tomomi, Sunao Sugiyama, Surhud More, et al.. (2024). Optical cluster cosmology with SDSS redMaPPer clusters and HSC-Y3 lensing measurements. Physical review. D. 110(8). 6 indexed citations
5.
Gao, Hua, et al.. (2024). IllustrisTNG in the HSC-SSP: No Shortage of Thin Disk Galaxies in TNG50. The Astrophysical Journal. 974(1). 88–88. 2 indexed citations
6.
Lee, Khee‐Gan, et al.. (2023). Alignments between Galaxies and the Cosmic Web at z ∼ 1–2 in the IllustrisTNG Simulations. The Astrophysical Journal. 954(1). 49–49. 6 indexed citations
7.
Bottrell, Connor, Hassen M. Yesuf, Gergö Popping, et al.. (2023). IllustrisTNG in the HSC-SSP: image data release and the major role of mini mergers as drivers of asymmetry and star formation. Monthly Notices of the Royal Astronomical Society. 527(3). 6506–6539. 33 indexed citations
8.
Shi, Jingjing, Yingjie Peng, Benedikt Diemer, et al.. (2022). Cold Gas in Massive Galaxies as a Critical Test of Black Hole Feedback Models. The Astrophysical Journal. 927(2). 189–189. 8 indexed citations
9.
Wang, Wenting, Zhaozhou Li, Jiaxin Han, et al.. (2022). A machine learning approach to infer the accreted stellar mass fractions of central galaxies in the TNG100 simulation. Monthly Notices of the Royal Astronomical Society. 515(3). 3938–3955. 8 indexed citations
10.
Wang, Huiyuan, Wentao Luo, H. J. Mo, et al.. (2021). Hosts and triggers of AGNs in the Local Universe. Astronomy and Astrophysics. 650. A155–A155. 19 indexed citations
11.
Li, Junyao, J. D. Silverman, Xuheng Ding, et al.. (2021). Synchronized Co-evolution between Supermassive Black Holes and Galaxies Over the Last Seven Billion Years as Revealed by the Hyper Suprime-Cam. arXiv (Cornell University). 29 indexed citations
12.
Peng, Yingjie, Luis C. Ho, R. Maiolino, et al.. (2021). Mass and Environment as Drivers of Galaxy Evolution. IV. On the Quenching of Massive Central Disk Galaxies in the Local Universe. Apollo (University of Cambridge). 13 indexed citations
13.
Wang, Wenting, Xiangchong Li, Jingjing Shi, et al.. (2021). The Stellar Mass in and around Isolated Central Galaxies: Connections to the Total Mass Distribution through Galaxy–Galaxy Lensing in the Hyper Suprime-Cam Survey. The Astrophysical Journal. 919(1). 25–25. 12 indexed citations
14.
Zhang, Lei, et al.. (2021). A multiple soil properties oriented representative sampling strategy for digital soil mapping. Geoderma. 406. 115531–115531. 22 indexed citations
15.
Wang, Wenting, Masahiro Takada, Xiangchong Li, et al.. (2020). A comparative study of satellite galaxies in Milky Way-like galaxies from HSC, DECaLS, and SDSS. Monthly Notices of the Royal Astronomical Society. 500(3). 3776–3801. 22 indexed citations
16.
Li, Ye, Bing Zhang, Kentaro Nagamine, & Jingjing Shi. (2019). The FRB 121102 Host Is Atypical among Nearby Fast Radio Bursts. Digital Scholarship - UNLV (University of Nevada Reno). 20 indexed citations
17.
Shi, Jingjing, Huiyuan Wang, H. J. Mo, et al.. (2018). Bimodal Formation Time Distribution for Infall Dark Matter Halos. The Astrophysical Journal. 857(2). 127–127. 2 indexed citations
18.
Shi, Jingjing & Ravi K. Sheth. (2017). Dependence of halo bias on mass and environment. Monthly Notices of the Royal Astronomical Society. 473(2). 2486–2492. 25 indexed citations
19.
Shi, Jingjing, Huiyuan Wang, & H. J. Mo. (2015). FLOW PATTERNS AROUND DARK MATTER HALOS: THE LINK BETWEEN HALO DYNAMICAL PROPERTIES AND LARGE-SCALE TIDAL FIELD. The Astrophysical Journal. 807(1). 37–37. 28 indexed citations
20.
Lei, Yinru, et al.. (2012). Efficiency of adaptive cluster sampling and traditional sampling for coastal mangrove in Hainan of China. Journal of Forest Science. 58(9). 381–390. 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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