James C. Knight

672 citations
31 papers · 355 indexed · h-index 11

James C. Knight

26 papers receiving 347 citations

Peers

James C. Knight
Comparison fields: 5 of 54
  • Cognitive Neuroscience 169
  • Cellular and Molecular Neuroscience 108
  • Electrical and Electronic Engineering 236
  • Artificial Intelligence 94
  • Computational Mathematics 1
Replace Francisco Naveros with:
Francisco Naveros Spain
Max Talanov Russia
Eric Hunsberger Canada
David Kappel Germany
Adrian Whatley Switzerland
Pierre Enel France
Dongsung Huh United States
Kaylo T. Littlejohn United States
Miguel Angrick United States
Shirin Dora United Kingdom
James C. Knight relative to Francisco Naveros Spain Francisco Naveros's profile →
Citations per field
00.5×
Francisco Naveros · 1×
Citations per year

Countries citing papers authored by James C. Knight

Since Specialization
Citations

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

Fields of papers citing papers by James C. Knight

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James C. Knight. 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 James C. Knight. The network helps show where James C. Knight may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20256
2 20251
3 20250
4 20241
5 20241
6 20241
7 20246
8 20240
9 20230
10 20234
11 20234
12 20227
13 202134
14 202014
15 20197
16 20181
17 201823
18 201854
19 201617
20 201619

About James C. Knight

James C. Knight is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering, having authored 31 papers that have together received 355 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (19 papers), Neural dynamics and brain function (16 papers), Ferroelectric and Negative Capacitance Devices (10 papers), Neurobiology and Insect Physiology Research (6 papers), Neural Networks and Applications (4 papers), Photoreceptor and optogenetics research (3 papers), Neural Networks and Reservoir Computing (3 papers) and Robotics and Sensor-Based Localization (3 papers). The work is most often cited by research in Cognitive Neuroscience (169 citations), Cellular and Molecular Neuroscience (108 citations) and Electrical and Electronic Engineering (236 citations). James C. Knight has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Thomas Nowotny, Steve Furber, Terrence C. Stewart, Brian Magerko, Illah Nourbakhsh, Paul Graham, Andrew Philippides, James P. Turner, Anders Lansner and Phil Husbands. Their work appears in journals such as Nature Communications, Current Biology and Cerebral Cortex.

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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