Michael Shaw

6.8k total citations
127 papers, 2.6k citations indexed

About

Michael Shaw is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Biomedical Engineering. According to data from OpenAlex, Michael Shaw has authored 127 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Electrical and Electronic Engineering, 34 papers in Atomic and Molecular Physics, and Optics and 18 papers in Biomedical Engineering. Recurrent topics in Michael Shaw's work include Photonic and Optical Devices (15 papers), Advanced Fluorescence Microscopy Techniques (10 papers) and Laser Design and Applications (10 papers). Michael Shaw is often cited by papers focused on Photonic and Optical Devices (15 papers), Advanced Fluorescence Microscopy Techniques (10 papers) and Laser Design and Applications (10 papers). Michael Shaw collaborates with scholars based in United States, United Kingdom and Sweden. Michael Shaw's co-authors include Gek Woo Tan, Chandrasekar Subramaniam, Michael Welge, Kevin O’Holleran, Michael R. Watts, Selwyn Piramuthu, Jeremy B. Wright, Erman Timurdogan, Aleksandr Biberman and Jong Woo Kim and has published in prestigious journals such as Angewandte Chemie International Edition, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Michael Shaw

121 papers receiving 2.4k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Michael Shaw 619 543 356 329 275 127 2.6k
Nan Li 236 0.4× 227 0.4× 202 0.6× 57 0.2× 887 3.2× 176 3.0k
Klaus Mueller 222 0.4× 242 0.4× 962 2.7× 128 0.4× 587 2.1× 268 6.4k
G. Beni 1.7k 2.7× 1.1k 1.9× 591 1.7× 158 0.5× 1.5k 5.5× 117 7.1k
Sang‐Chul Lee 632 1.0× 87 0.2× 343 1.0× 33 0.1× 145 0.5× 163 2.6k
Jie Bao 865 1.4× 235 0.4× 895 2.5× 43 0.1× 693 2.5× 159 5.0k
Matthew N. O. Sadiku 1.5k 2.5× 418 0.8× 373 1.0× 59 0.2× 229 0.8× 310 3.3k
Gordon E. Moore 2.7k 4.4× 702 1.3× 700 2.0× 296 0.9× 391 1.4× 57 5.8k
Jie Ren 857 1.4× 2.5k 4.5× 881 2.5× 111 0.3× 557 2.0× 187 7.6k
P. V. Johnson 536 0.9× 512 0.9× 124 0.3× 289 0.9× 104 0.4× 156 3.6k
Sheng Liu 729 1.2× 168 0.3× 617 1.7× 44 0.1× 136 0.5× 318 3.6k

Countries citing papers authored by Michael Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Michael Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Shaw. A scholar is included among the top collaborators of Michael Shaw 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 Shaw. Michael Shaw 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.
Hasan, Erol, Stéphanie Rey, James E. Noble, et al.. (2025). A self-assembled protein β-helix as a self-contained biofunctional motif. Nature Communications. 16(1). 4535–4535. 1 indexed citations
2.
Faruqui, Nilofar, Zaira Leni, Jenny Rissler, et al.. (2025). Differential Cytotoxicity and Inflammatory Responses to Particulate Matter Components in Airway Structural Cells. International Journal of Molecular Sciences. 26(2). 830–830. 4 indexed citations
3.
Vorng, Jean‐Luc, Natalie A. Belsey, G. McMahon, et al.. (2025). Multiparametric physicochemical analysis of a type 1 collagen 3D cell culture model using light and electron microscopy and mass spectrometry imaging. Scientific Reports. 15(1). 9578–9578. 2 indexed citations
4.
Al‐Rekabi, Zeinab, Nilofar Faruqui, Linda Elowsson, et al.. (2023). Uncovering the cytotoxic effects of air pollution with multi-modal imaging of in vitro respiratory models. Royal Society Open Science. 10(4). 221426–221426. 9 indexed citations
5.
6.
Pawar, Vijay, et al.. (2023). Minimum resolution requirements of digital pathology images for accurate classification. Medical Image Analysis. 89. 102891–102891. 5 indexed citations
7.
Shaw, Michael, et al.. (2022). Time-Dependent Studies of Oxaliplatin and Other Nucleolar Stress-Inducing Pt(II) Derivatives. ACS Chemical Biology. 17(8). 2262–2271. 11 indexed citations
8.
El‐Sayed, Mohamed Y., Harrison Edwards, Shuailong Zhang, et al.. (2022). Adaptive Autonomous Navigation of Multiple Optoelectronic Microrobots in Dynamic Environments. IEEE Robotics and Automation Letters. 7(4). 11102–11109. 6 indexed citations
9.
Romanchikova, Marina, et al.. (2022). The need for measurement science in digital pathology. Journal of Pathology Informatics. 13. 100157–100157. 10 indexed citations
10.
Shaw, Michael, et al.. (2021). mmSIM: an open toolbox for accessible structured illumination microscopy. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 379(2199). 20200353–20200353. 2 indexed citations
11.
Essmann, Clara L., Sophia Bano, Neil T. Clancy, et al.. (2021). Stain-free identification of tissue pathology using a generative adversarial network to infer nanomechanical signatures. Nanoscale Advances. 3(22). 6403–6414. 1 indexed citations
12.
Corbett, Alexander D., Michael Shaw, Andrew Yacoot, et al.. (2018). Microscope calibration using laser written fluorescence. Optics Express. 26(17). 21887–21887. 23 indexed citations
13.
Longatti, Andrea, Christina Schindler, Lesley Jenkinson, et al.. (2018). High affinity single-chain variable fragments are specific and versatile targeting motifs for extracellular vesicles. Nanoscale. 10(29). 14230–14244. 86 indexed citations
14.
Shaw, Michael, Nilofar Faruqui, Angelo Bella, et al.. (2016). Nano-mechanical single-cell sensing of cell–matrix contacts. Nanoscale. 8(42). 18105–18112. 6 indexed citations
15.
Shaw, Michael, Muna Elmi, Vijay Pawar, & Mandayam A. Srinivasan. (2016). Investigation of mechanosensation in C elegans using light field calcium imaging. Biomedical Optics Express. 7(7). 2877–2877. 5 indexed citations
16.
O’Holleran, Kevin & Michael Shaw. (2014). Optimized approaches for optical sectioning and resolution enhancement in 2D structured illumination microscopy. Biomedical Optics Express. 5(8). 2580–2580. 52 indexed citations
17.
Kumar, Sujay V., et al.. (2012). Land surface Verification Toolkit (LVT) – a generalized framework for land surface model evaluation. Geoscientific model development. 5(3). 869–886. 51 indexed citations
18.
Shaw, Michael, et al.. (2012). Three-Dimensional Cell Morphometry for the Quantification of Cell–Substrate Interactions. Tissue Engineering Part C Methods. 19(1). 48–56. 3 indexed citations
19.
Rubenstein, Marvin, et al.. (1995). Orthotopic placement of the dunning R3327 AT‐3 prostate tumor in the copenhagen X fischer rat. The Prostate. 27(3). 148–153. 5 indexed citations
20.
Shaw, Michael & Andrew B. Whinston. (1990). Learning and adaption in distributed artificial intelligence. Morgan Kaufmann Publishers Inc. eBooks. 413–429. 6 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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