Mark McLean

20 papers receiving 443 citations

Peers

Mark McLean
Comparison fields: 5 of 47
  • Signal Processing 142
  • Geometry and Topology 103
  • Mathematical Physics 79
  • Computer Networks and Communications 127
  • Artificial Intelligence 156
Replace Stephen F. Siegel with:
Stephen F. Siegel United States
Jing Qiu China
Zheng Huang China
Vince Lyzinski United States
Türker Bı́yı́koğlu Türkiye
Wafaa S. Sayed Egypt
Daniel Barsky United States
Jonathan Ashley United States
Manabu Hagiwara Japan
Michael Tarsi Israel
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Citations per field
00.5×10×12.9×
Stephen F. Siegel · 1×
Citations per year

Countries citing papers authored by Mark McLean

Since Specialization
Citations

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

Fields of papers citing papers by Mark McLean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Mark McLean, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark McLean Line = papers co-authored together Mark McLean links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016116
2 201974
3 201351
4 201436
5 200929
6 201927
7 201720
8 201519
9 201418
10 201217
11 201815
12 200912
13 201210
14 20119
15 20115
16 20144
17 20183
18 20192
19 20202
20 20181

About Mark McLean

Mark McLean is a scholar working on Geometry and Topology, Mathematical Physics, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 22 papers that have together received 470 indexed citations. Recurring topics across this work include Geometric and Algebraic Topology (9 papers), Algebraic Geometry and Number Theory (8 papers), Homotopy and Cohomology in Algebraic Topology (7 papers), Advanced Memory and Neural Computing (6 papers), Neuroscience and Neural Engineering (5 papers), CCD and CMOS Imaging Sensors (3 papers), Advanced Malware Detection Techniques (2 papers) and Ferroelectric and Negative Capacitance Devices (2 papers). The work is most often cited by research in Signal Processing (142 citations), Geometry and Topology (103 citations), Mathematical Physics (79 citations), Computer Networks and Communications (127 citations) and Artificial Intelligence (156 citations). Mark McLean has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Edward Raff, Jared Sylvester, Chris Yakopcic, Raqibul Hasan, Tarek M. Taha, Charles Nicholas, Richard Zak, D.A. Palmer, Christopher D. Krieger and Matthew Marinella. Their work appears in journals such as Geometry & Topology, Geometric and Functional Analysis, Journal of Computer Virology and Hacking Techniques, Inventiones mathematicae and Computational Geosciences.

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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