Liam McDaid

2.4k citations
140 papers · 1.9k · h-index 23

Impact in

Papers in

Liam McDaid

130 papers receiving 1.8k citations

Peers

Liam McDaid
Comparison fields: 5 of 114
  • Cellular and Molecular Neuroscience 852
  • Cognitive Neuroscience 763
  • Electrical and Electronic Engineering 1.3k
  • Neurology 112
  • Artificial Intelligence 337
Replace Jim Harkin with:
Jim Harkin United Kingdom
Daniel Soudry Israel
Jonathan Tapson Australia
Felix Schürmann Switzerland
Friedemann Zenke Switzerland
Francesco Galluppi United Kingdom
Steven K. Esser United States
Eugenio Culurciello United States
Dong Song United States
Johannes Schemmel Germany
Liam McDaid relative to Jim Harkin United Kingdom Jim Harkin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Liam McDaid

Since Specialization
Citations

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

Fields of papers citing papers by Liam McDaid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Liam McDaid, 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 Liam McDaid Line = papers co-authored together Liam McDaid links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 140 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010153
2 2011109
3 2012104
4 198998
5 201255
6 201855
7 201755
8 200943
9 201843
10 201242
11 201640
12 201740
13 201540
14 201139
15 201039
16 201832
17 201230
18 202029
19 201028
20 201227

About Liam McDaid

Liam McDaid is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience, Artificial Intelligence and Computer Networks and Communications, having authored 140 papers that have together received 1.9k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (90 papers), Neural dynamics and brain function (64 papers), Neuroscience and Neural Engineering (60 papers), Advancements in Semiconductor Devices and Circuit Design (16 papers), Semiconductor materials and devices (15 papers), Neuroscience and Neuropharmacology Research (14 papers), Neural Networks and Applications (13 papers) and CCD and CMOS Imaging Sensors (12 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (852 citations), Cognitive Neuroscience (763 citations), Electrical and Electronic Engineering (1.3k citations), Neurology (112 citations) and Artificial Intelligence (337 citations). Liam McDaid has collaborated with scholars based in United Kingdom, Ireland and United States. Frequent co-authors include Jim Harkin, John Wade, Junxiu Liu, Liam Maguire, Fearghal Morgan, Seamus Cawley, Brian McGinley, José Santos, Sandeep Dwarkanath Pande and S. Hall. Their work appears in journals such as Neurocomputing, Electronics Letters, IEEE Transactions on Neural Networks and Learning Systems, Frontiers in Cellular Neuroscience and PLoS Computational Biology.

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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