Michael Ridley

639 total citations
19 papers, 468 citations indexed

About

Michael Ridley is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Molecular Biology. According to data from OpenAlex, Michael Ridley has authored 19 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Atomic and Molecular Physics, and Optics, 8 papers in Electrical and Electronic Engineering and 4 papers in Molecular Biology. Recurrent topics in Michael Ridley's work include Molecular Junctions and Nanostructures (8 papers), Quantum and electron transport phenomena (8 papers) and Advancements in Semiconductor Devices and Circuit Design (4 papers). Michael Ridley is often cited by papers focused on Molecular Junctions and Nanostructures (8 papers), Quantum and electron transport phenomena (8 papers) and Advancements in Semiconductor Devices and Circuit Design (4 papers). Michael Ridley collaborates with scholars based in United Kingdom, Israel and United States. Michael Ridley's co-authors include Lev Kantorovich, A. MacKinnon, Emanuel Gull, Guy Cohen, Leonie S. Taams, Kathryn J. A. Steel, Ewan A. Ross, Andrew R. Clark, Jonathan L. E. Dean and Christopher D. Buckley and has published in prestigious journals such as The Journal of Immunology, Molecular and Cellular Biology and Physical Review B.

In The Last Decade

Michael Ridley

18 papers receiving 463 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Ridley United Kingdom 13 149 149 132 84 61 19 468
Zhong Guan China 14 300 2.0× 44 0.3× 213 1.6× 68 0.8× 7 0.1× 57 786
Masataka Shirai Japan 10 151 1.0× 50 0.3× 76 0.6× 43 0.5× 23 0.4× 29 365
S. Krüger Germany 11 47 0.3× 50 0.3× 153 1.2× 24 0.3× 12 0.2× 25 462
Dongyang Jiang China 13 161 1.1× 85 0.6× 35 0.3× 9 0.1× 11 0.2× 34 390
Kento Kawasaki Japan 10 106 0.7× 68 0.5× 77 0.6× 16 0.2× 24 0.4× 24 428
Yuki Kikuchi Japan 8 119 0.8× 47 0.3× 60 0.5× 40 0.5× 12 0.2× 41 487
Fuqu Yu United States 11 173 1.2× 117 0.8× 47 0.4× 73 0.9× 24 0.4× 15 710
Sidney P. Elmer United States 10 358 2.4× 77 0.5× 62 0.5× 4 0.0× 30 0.5× 12 733
Nao Nitta Japan 10 141 0.9× 158 1.1× 65 0.5× 43 0.5× 7 0.1× 18 638
A. Franchi Italy 16 341 2.3× 57 0.4× 48 0.4× 177 2.1× 6 0.1× 50 836

Countries citing papers authored by Michael Ridley

Since Specialization
Citations

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

Fields of papers citing papers by Michael Ridley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Ridley

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

All Works

19 of 19 papers shown
1.
Ridley, Michael, et al.. (2025). Photon-assisted stochastic resonance in nanojunctions. Physical review. B.. 111(9). 1 indexed citations
2.
Ridley, Michael & Emily Adlam. (2024). Time and event symmetry in quantum mechanics. Quantum Studies Mathematics and Foundations. 12(1).
3.
Ridley, Michael, Lev Kantorovich, Robert van Leeuwen, & Riku Tuovinen. (2021). Quantum interference and the time-dependent radiation of nanojunctions. Physical review. B.. 103(11). 12 indexed citations
4.
Povoleri, Giovanni A. M., Domenico Somma, Michael Ridley, et al.. (2021). miR-155-overexpressing monocytes resemble HLAhighISG15+ synovial tissue macrophages from patients with rheumatoid arthritis and induce polyfunctional CD4+ T-cell activation. Clinical & Experimental Immunology. 207(2). 188–198. 10 indexed citations
5.
Aharonov, Yakir, et al.. (2021). Failed attempt to escape from the quantum pigeon conundrum. Physics Letters A. 399. 127287–127287. 1 indexed citations
6.
Ridley, Michael, Veerle Fleskens, Ceri A. Roberts, et al.. (2020). IKZF3/Aiolos Is Associated with but Not Sufficient for the Expression of IL-10 by CD4+ T Cells. The Journal of Immunology. 204(11). 2940–2948. 19 indexed citations
7.
Povoleri, Giovanni A. M., Sylvine Lalnunhlimi, Kathryn J. A. Steel, et al.. (2019). Anti‐TNF treatment negatively regulates human CD4 + T‐cell activation and maturation in vitro, but does not confer an anergic or suppressive phenotype. European Journal of Immunology. 50(3). 445–458. 17 indexed citations
8.
Ridley, Michael, Michael Galperin, Emanuel Gull, & Guy Cohen. (2019). Numerically exact full counting statistics of the energy current in the Kondo regime. Physical review. B.. 100(16). 21 indexed citations
9.
Steel, Kathryn J. A., Ushani Srenathan, Michael Ridley, et al.. (2019). Polyfunctional, Proinflammatory, Tissue‐Resident Memory Phenotype and Function of Synovial Interleukin‐17A+CD8+ T Cells in Psoriatic Arthritis. Arthritis & Rheumatology. 72(3). 435–447. 92 indexed citations
10.
Ridley, Michael, et al.. (2018). Numerically exact full counting statistics of the nonequilibrium Anderson impurity model. Physical review. B.. 97(11). 38 indexed citations
11.
Ridley, Michael & Riku Tuovinen. (2017). Time-dependent Landauer-Büttiker approach to charge pumping in ac-driven graphene nanoribbons. Physical review. B.. 96(19). 12 indexed citations
12.
O’Neil, John D., Ewan A. Ross, Michael Ridley, et al.. (2017). Gain-of-Function Mutation of Tristetraprolin Impairs Negative Feedback Control of Macrophages In Vitro yet Has Overwhelmingly Anti-Inflammatory Consequences In Vivo. Molecular and Cellular Biology. 37(11). 41 indexed citations
13.
Ridley, Michael, A. MacKinnon, & Lev Kantorovich. (2017). Partition-free theory of time-dependent current correlations in nanojunctions in response to an arbitrary time-dependent bias. Physical review. B.. 95(16). 19 indexed citations
14.
Ross, Ewan A., Amy J. Naylor, John D. O’Neil, et al.. (2016). Treatment of inflammatory arthritis via targeting of tristetraprolin, a master regulator of pro-inflammatory gene expression. Annals of the Rheumatic Diseases. 76(3). 612–619. 62 indexed citations
15.
Ridley, Michael, A. MacKinnon, & Lev Kantorovich. (2016). Fluctuating-bias controlled electron transport in molecular junctions. Physical review. B.. 93(20). 12 indexed citations
16.
Ridley, Michael, A. MacKinnon, & Lev Kantorovich. (2016). Calculation of the current response in a nanojunction for an arbitrary time-dependent bias: application to the molecular wire. Journal of Physics Conference Series. 696. 12017–12017. 9 indexed citations
17.
Ridley, Michael, A. MacKinnon, & Lev Kantorovich. (2015). Current through a multilead nanojunction in response to an arbitrary time-dependent bias. Physical Review B. 91(12). 30 indexed citations
18.
Smallie, Tim, Ewan A. Ross, Alaina J. Ammit, et al.. (2015). Dual-Specificity Phosphatase 1 and Tristetraprolin Cooperate To Regulate Macrophage Responses to Lipopolysaccharide. The Journal of Immunology. 195(1). 277–288. 59 indexed citations
19.
Briggs, Deborah A., et al.. (2011). Induction of a stress response in Lactococcus lactis is associated with a resistance to ribosomally active antibiotics. FEBS Journal. 278(21). 4015–4024. 13 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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