Y. Shu

927 total citations
43 papers, 537 citations indexed

About

Y. Shu is a scholar working on Astronomy and Astrophysics, Instrumentation and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Y. Shu has authored 43 papers receiving a total of 537 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Astronomy and Astrophysics, 20 papers in Instrumentation and 7 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Y. Shu's work include Galaxies: Formation, Evolution, Phenomena (31 papers), Astronomy and Astrophysical Research (19 papers) and Gamma-ray bursts and supernovae (12 papers). Y. Shu is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (31 papers), Astronomy and Astrophysical Research (19 papers) and Gamma-ray bursts and supernovae (12 papers). Y. Shu collaborates with scholars based in China, United Kingdom and Germany. Y. Shu's co-authors include A. Bolton, Antonio D. Montero-Dorta, Ran Li, Joel R. Brownstein, R. Marques-Chaves, Xiaoyue Cao, I. Pérez‐Fournon, Rui Li, Jiancheng Wang and Matthew W. Auger and has published in prestigious journals such as The Astrophysical Journal, Scientific Reports and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Y. Shu

36 papers receiving 492 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Y. Shu China 13 474 233 102 39 30 43 537
Fumihiro Uraguchi Japan 10 475 1.0× 202 0.9× 75 0.7× 49 1.3× 29 1.0× 42 538
J.W Nightingale United Kingdom 16 554 1.2× 217 0.9× 142 1.4× 60 1.5× 32 1.1× 35 606
T. Anguita Chile 16 598 1.3× 235 1.0× 92 0.9× 76 1.9× 20 0.7× 40 634
Leonardo Ferreira United Kingdom 14 583 1.2× 377 1.6× 43 0.4× 65 1.7× 30 1.0× 38 666
C. F. Claver United States 9 349 0.7× 174 0.7× 82 0.8× 22 0.6× 17 0.6× 35 440
C. Bonnett United Kingdom 3 454 1.0× 168 0.7× 40 0.4× 103 2.6× 35 1.2× 3 504
S. Paulin‐Henriksson France 14 595 1.3× 223 1.0× 167 1.6× 71 1.8× 39 1.3× 20 634
Nuria P. F. Lorente Australia 12 511 1.1× 283 1.2× 43 0.4× 60 1.5× 23 0.8× 28 558
T. M. C. Abbott Chile 2 414 0.9× 144 0.6× 34 0.3× 101 2.6× 30 1.0× 2 464
Jielai Zhang United States 13 660 1.4× 308 1.3× 40 0.4× 119 3.1× 16 0.5× 28 706

Countries citing papers authored by Y. Shu

Since Specialization
Citations

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

Fields of papers citing papers by Y. Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Y. Shu

This figure shows the co-authorship network connecting the top 25 collaborators of Y. Shu. A scholar is included among the top collaborators of Y. Shu 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 Y. Shu. Y. Shu 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.
Deng, Libin, et al.. (2025). Discovery of 19 strongly lensed, dual, or projected quasars in DESI-LS. Astronomy and Astrophysics. 695. A76–A76.
2.
Shan, Huanyuan, Y. Shu, Ji Yao, et al.. (2025). CURLING – II. Improvement on the H 0 inference from pixelized cluster strong lens modelling. Monthly Notices of the Royal Astronomical Society. 544(1). 708–716.
3.
Lei, Lei, et al.. (2025). A Dense Dark Matter Core of the Subhalo in the Strong Lensing System JVAS B1938+666. The Astrophysical Journal Letters. 991(1). L27–L27. 1 indexed citations
4.
Deng, Liqun, et al.. (2025). Discovery of a Low-mass Strong-lens System in SMACS J0723.3−7327. The Astrophysical Journal Letters. 982(1). L23–L23.
5.
Shu, Y., et al.. (2025). FreeDOM: Online Dynamic Object Removal Framework for Static Map Construction Based on Conservative Free Space Estimation. IEEE Robotics and Automation Letters. 10(6). 5577–5584. 1 indexed citations
6.
Schuldt, S., Y. Shu, S. Taubenberger, et al.. (2024). HOLISMOKES. Astronomy and Astrophysics. 692. A72–A72. 6 indexed citations
7.
Lemon, Cameron, F. Courbin, Anupreeta More, et al.. (2024). Searching for Strong Gravitational Lenses. Space Science Reviews. 220(2). 9 indexed citations
8.
Schuldt, S., S. H. Suyu, R. Cañameras, et al.. (2023). HOLISMOKES. Astronomy and Astrophysics. 673. A33–A33. 9 indexed citations
9.
Du, Wei, et al.. (2023). Mass Reconstruction of Galaxy-scale Strong Gravitational Lenses Using a Broken Power-law Model. The Astrophysical Journal. 953(2). 189–189. 3 indexed citations
10.
Huang, Xiaosheng, William Sheu, G. Aldering, et al.. (2022). GIGA-Lens: Fast Bayesian Inference for Strong Gravitational Lens Modeling. The Astrophysical Journal. 935(1). 49–49. 25 indexed citations
11.
Shu, Y., et al.. (2021). Discovery of two bright high-redshift gravitationally lensed quasars revealed by Gaia. Monthly Notices of the Royal Astronomical Society. 509(1). 738–747. 5 indexed citations
12.
Cao, Xiaoyue, Ran Li, Y. Shu, et al.. (2020). LESSER: a catalogue of spectroscopically selected sample of Lyman-α emitters lensed by galaxies. Monthly Notices of the Royal Astronomical Society. 499(3). 3610–3619. 14 indexed citations
13.
Marques-Chaves, R., Javier Álvarez-Márquez, L. Colina, et al.. (2020). The discovery of the most UV–Ly α luminous star-forming galaxy: a young, dust- and metal-poor starburst with QSO-like luminosities. Monthly Notices of the Royal Astronomical Society Letters. 499(1). L105–L110. 15 indexed citations
14.
Chen, Yun, Ran Li, Y. Shu, & Xiaoyue Cao. (2019). Assessing the effect of lens mass model in cosmological application with updated galaxy-scale strong gravitational lensing sample. Monthly Notices of the Royal Astronomical Society. 488(3). 3745–3758. 47 indexed citations
15.
Shu, Y., S. E. Koposov, N. W. Evans, et al.. (2019). Catalogues of active galactic nuclei from Gaia and unWISE data. Monthly Notices of the Royal Astronomical Society. 489(4). 4741–4759. 38 indexed citations
16.
Marques-Chaves, R., I. Pérez‐Fournon, Y. Shu, et al.. (2019). Rest-frame UV properties of luminous strong gravitationally lensed Lyα emitters from the BELLS GALLERY Survey. Monthly Notices of the Royal Astronomical Society. 492(1). 1257–1278. 16 indexed citations
17.
Marques-Chaves, R., I. Pérez‐Fournon, M. Villar-Martı́n, et al.. (2019). Discovery of a giant and luminous Lyα+C IV+He II nebula at z = 3.326 with extreme emission line ratios. Astronomy and Astrophysics. 629. A23–A23. 8 indexed citations
18.
Du, Wei, Gong‐Bo Zhao, Zuhui Fan, et al.. (2019). An accurate analytic model for the lensing mass of galaxies. arXiv (Cornell University). 2 indexed citations
19.
Marques-Chaves, R., I. Pérez‐Fournon, Y. Shu, et al.. (2017). Discovery of a Very Bright and Intrinsically Very Luminous, Strongly Lensed Lyα Emitting Galaxy at z = 2.82 in the BOSS Emission-Line Lens Survey*. The Astrophysical Journal Letters. 834(2). L18–L18. 12 indexed citations
20.
Shu, Y., A. Bolton, Shude Mao, et al.. (2016). THE BOSS EMISSION-LINE LENS SURVEY. IV. SMOOTH LENS MODELS FOR THE BELLS GALLERY SAMPLE*. The Astrophysical Journal. 833(2). 264–264. 68 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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