Jonathan R. Walsh

4.3k total citations
39 papers, 1.7k citations indexed

About

Jonathan R. Walsh is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Surgery. According to data from OpenAlex, Jonathan R. Walsh has authored 39 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Nuclear and High Energy Physics, 4 papers in Astronomy and Astrophysics and 3 papers in Surgery. Recurrent topics in Jonathan R. Walsh's work include Particle physics theoretical and experimental studies (19 papers), High-Energy Particle Collisions Research (15 papers) and Quantum Chromodynamics and Particle Interactions (13 papers). Jonathan R. Walsh is often cited by papers focused on Particle physics theoretical and experimental studies (19 papers), High-Energy Particle Collisions Research (15 papers) and Quantum Chromodynamics and Particle Interactions (13 papers). Jonathan R. Walsh collaborates with scholars based in United States, Germany and United Kingdom. Jonathan R. Walsh's co-authors include Stephen Ellis, Christopher K. Vermilion, Frank J. Tackmann, Saba Zuberi, Christopher Lee, Andrew Hornig, C. Bauer, Maximilian Stahlhofen, Jonathan R. Gaunt and Iain W. Stewart and has published in prestigious journals such as Science, Journal of Cleaner Production and Physics Letters B.

In The Last Decade

Jonathan R. Walsh

37 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan R. Walsh United States 22 1.4k 167 70 58 52 39 1.7k
R. Richter Germany 17 890 0.6× 227 1.4× 18 0.3× 132 2.3× 36 0.7× 68 1.0k
T. Uckan United States 13 417 0.3× 221 1.3× 94 1.3× 122 2.1× 52 1.0× 71 614
M. Williams United States 10 573 0.4× 127 0.8× 85 1.2× 43 0.7× 10 0.2× 24 724
Johann Brehmer United States 12 454 0.3× 100 0.6× 149 2.1× 30 0.5× 14 0.3× 23 600
Grégory Soyez France 27 2.1k 1.5× 125 0.7× 93 1.3× 18 0.3× 23 0.4× 72 2.2k
P. Greenfield United States 16 171 0.1× 525 3.1× 35 0.5× 34 0.6× 16 0.3× 62 737
Alfonso G. Tarditi United States 9 405 0.3× 573 3.4× 30 0.4× 142 2.4× 75 1.4× 27 826
Xiao-Dong Li China 18 829 0.6× 1.3k 7.5× 42 0.6× 72 1.2× 29 0.6× 64 1.7k
S. Uchaikin Germany 15 155 0.1× 77 0.5× 358 5.1× 102 1.8× 35 0.7× 48 757
I. Lupelli United Kingdom 17 383 0.3× 109 0.7× 42 0.6× 30 0.5× 84 1.6× 61 647

Countries citing papers authored by Jonathan R. Walsh

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan R. Walsh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan R. Walsh. 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 Jonathan R. Walsh. The network helps show where Jonathan R. Walsh may publish in the future.

Co-authorship network of co-authors of Jonathan R. Walsh

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan R. Walsh. A scholar is included among the top collaborators of Jonathan R. Walsh 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 Jonathan R. Walsh. Jonathan R. Walsh 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
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Pasqualini, Ignacio, et al.. (2025). Utilization of Total Knee Arthroplasty in the United States by Settlement Type: Is There Equity of Access?. Journal of the American Academy of Orthopaedic Surgeons. 33(21). 1208–1212. 1 indexed citations
3.
4.
Walsh, Jonathan R., et al.. (2024). Femoral stem extraction devices. Archives of Orthopaedic and Trauma Surgery. 145(1). 27–27.
5.
Fisher, Charles K., et al.. (2024). Increasing acceptance of AI‐generated digital twins through clinical trial applications. Clinical and Translational Science. 17(7). e13897–e13897. 28 indexed citations
6.
Walsh, Jonathan R. & Lucy Berthoud. (2023). Distribution of Atomic Oxygen within the Internal Cavities of VLEO Satellites. Bristol Research (University of Bristol). 1.2. 1–17.
7.
Walsh, Jonathan R., John M. Long, Craig B. Davis, et al.. (2020). Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data. BMC Bioinformatics. 21(1). 119–119. 47 indexed citations
8.
Davis, Stephanie D., Jonathan R. Walsh, Amelia F. Drake, et al.. (2020). Volumetric nasal cavity analysis in children with unilateral and bilateral cleft lip and palate: Nasal Cavity Volume in Cleft Lip and Palate. UNC Libraries. 1 indexed citations
9.
Berthoud, Lucy & Jonathan R. Walsh. (2020). Using visualisations to develop skills in astrodynamics. European Journal of Engineering Education. 45(6). 900–916. 7 indexed citations
10.
Fisher, Charles K., et al.. (2018). Using deep learning for comprehensive, personalized forecasting of Alzheimer's Disease progression.. arXiv (Cornell University). 1 indexed citations
11.
Bertolini, Daniele, Katelin Schutz, Mikhail P. Solon, Jonathan R. Walsh, & Kathryn M. Zurek. (2016). Non-Gaussian covariance of the matter power spectrum in the effective field theory of large scale structure. Physical review. D. 93(12). 46 indexed citations
12.
Alioli, Simone, C. Bauer, Calvin Berggren, Frank J. Tackmann, & Jonathan R. Walsh. (2015). Drell-Yan production atNNLL′+NNLOmatched to parton showers. Physical review. D. Particles, fields, gravitation, and cosmology. 92(9). 74 indexed citations
13.
Boughezal, Radja, Xiaohui Liu, F. Petriello, Frank J. Tackmann, & Jonathan R. Walsh. (2014). Combining resummed Higgs predictions across jet bins. Physical review. D. Particles, fields, gravitation, and cosmology. 89(7). 20 indexed citations
14.
Alioli, Simone, C. Bauer, Calvin Berggren, et al.. (2013). Combining higher-order resummation with multiple NLO calculations and parton showers in GENEVA. Journal of High Energy Physics. 2013(9). 76 indexed citations
15.
Hornig, Andrew, Iain W. Stewart, Christopher Lee, Jonathan R. Walsh, & Saba Zuberi. (2012). Non-global structure of the O(α2s) dijet soft function. DSpace@MIT (Massachusetts Institute of Technology). 36 indexed citations
16.
Kelley, R., Jonathan R. Walsh, & Saba Zuberi. (2012). Abelian non-global logarithms from soft gluon clustering. Journal of High Energy Physics. 2012(9). 29 indexed citations
17.
Ellis, Stephen, Andrew Hornig, Christopher Lee, Christopher K. Vermilion, & Jonathan R. Walsh. (2010). Consistent factorization of jet observables in exclusive multijet cross sections. Physics Letters B. 689(2-3). 82–89. 34 indexed citations
18.
Ellis, Stephen, Christopher K. Vermilion, & Jonathan R. Walsh. (2009). Techniques for improved heavy particle searches with jet substructure. Physical review. D. Particles, fields, gravitation, and cosmology. 80(5). 162 indexed citations
19.
Nelson, Ann E. & Jonathan R. Walsh. (2008). Chameleon vector bosons. Physical review. D. Particles, fields, gravitation, and cosmology. 77(9). 25 indexed citations
20.
Nelson, Ann E. & Jonathan R. Walsh. (2008). Short baseline neutrino oscillations and a new light gauge boson. Physical review. D. Particles, fields, gravitation, and cosmology. 77(3). 33 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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