M. S. Wang

4.6k total citations
10 papers, 138 citations indexed

About

M. S. Wang is a scholar working on Astronomy and Astrophysics, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, M. S. Wang has authored 10 papers receiving a total of 138 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Astronomy and Astrophysics, 3 papers in Artificial Intelligence and 3 papers in Biomedical Engineering. Recurrent topics in M. S. Wang's work include Cosmology and Gravitation Theories (6 papers), Galaxies: Formation, Evolution, Phenomena (4 papers) and Advanced Materials Characterization Techniques (2 papers). M. S. Wang is often cited by papers focused on Cosmology and Gravitation Theories (6 papers), Galaxies: Formation, Evolution, Phenomena (4 papers) and Advanced Materials Characterization Techniques (2 papers). M. S. Wang collaborates with scholars based in United Kingdom, United States and Spain. M. S. Wang's co-authors include K. E. Spear, Florian Beutler, David Bacon, S. Àvila, Will J. Percival, D. Bianchi, Alexandre Perera-Lluna, Ricardo Gutiérrez‐Osuna, Robert Crittenden and Mi Chang and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, IEEE Transactions on Electron Devices and Astronomy and Astrophysics.

In The Last Decade

M. S. Wang

10 papers receiving 126 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. S. Wang United Kingdom	7	57	31	29	15	15	10	138
V. Revéret France	8	106 1.9×	49 1.6×	8 0.3×	4 0.3×	7 0.5×	29	151
Takashi Hasebe Japan	5	25 0.4×	22 0.7×	11 0.4×	3 0.2×	5 0.3×	18	89
Robert Garwood United States	6	108 1.9×	18 0.6×	62 2.1×	19 1.3×	2 0.1×	14	201
M. Nordby United States	5	12 0.2×	51 1.6×	5 0.2×	12 0.8×	9 0.6×	22	103
M. Imori Japan	6	24 0.4×	33 1.1×	14 0.5×	2 0.1×	2 0.1×	22	120
Masashi Otsubo Japan	6	48 0.8×	40 1.3×	13 0.4×	15 1.0×	3 0.2×	12	112
Hui-Gen Liu China	9	126 2.2×	49 1.6×	5 0.2×	35 2.3×	8 0.5×	29	189
Peter Timbie United States	6	86 1.5×	51 1.6×	10 0.3×	1 0.1×	2 0.1×	14	142
William L. Eichhorn United States	5	33 0.6×	37 1.2×	20 0.7×	19 1.3×	1 0.1×	20	100

Countries citing papers authored by M. S. Wang

Since Specialization

Citations

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

Fields of papers citing papers by M. S. Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. S. Wang

This figure shows the co-authorship network connecting the top 25 collaborators of M. S. Wang. A scholar is included among the top collaborators of M. S. 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 M. S. Wang. M. S. 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:

10 of 10 papers shown

Wang, M. S., et al.. (2025). A comparison of shrinkage estimators of the cosmological precision matrix. Monthly Notices of the Royal Astronomical Society. 537(1). 21–34. 2 indexed citations

Adame, A. G., S. Àvila, Violeta González-Pérez, et al.. (2024). PNG-UNITsims: Halo clustering response to primordial non-Gaussianities as a function of mass. Astronomy and Astrophysics. 689. A69–A69. 5 indexed citations

Wang, M. S., Florian Beutler, & Naonori S. Sugiyama. (2023). Triumvirate: A Python/C++ package for three-pointclustering measurements. The Journal of Open Source Software. 8(91). 5571–5571. 4 indexed citations

Wang, M. S., Florian Beutler, & David Bacon. (2020). Impact of relativistic effects on the primordial non-Gaussianity signature in the large-scale clustering of quasars. Monthly Notices of the Royal Astronomical Society. 499(2). 2598–2607. 23 indexed citations

Wang, M. S., S. Àvila, D. Bianchi, Robert Crittenden, & Will J. Percival. (2020). Hybrid-basis inference for large-scale galaxy clustering: combining spherical and Cartesian Fourier analyses. Journal of Cosmology and Astroparticle Physics. 2020(10). 22–22. 12 indexed citations

Wang, M. S., Will J. Percival, S. Àvila, Robert Crittenden, & D. Bianchi. (2019). Cosmological inference from galaxy-clustering power spectrum: Gaussianization and covariance decomposition. Monthly Notices of the Royal Astronomical Society. 486(1). 951–965. 14 indexed citations

Wang, M. S., Alexandre Perera-Lluna, & Ricardo Gutiérrez‐Osuna. (2006). Principal discriminants analysis for small-sample-size problems: application to chemical sensing. 591–594. 16 indexed citations

Chang, Mi, et al.. (2005). Si–H Bond Breaking Induced Retention Degradation During Packaging Process of 256 Mbit DRAMs With Negative Wordline Bias. IEEE Transactions on Electron Devices. 52(4). 484–491. 27 indexed citations

Spear, K. E. & M. S. Wang. (1981). Thermodynamic modeling of the molybdenum-boron system. Calphad. 5(2). 109–113. 20 indexed citations

10.

Spear, K. E., et al.. (1981). Thermodynamic modeling of the VB system. Journal of the Less Common Metals. 82. 237–243. 15 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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