Greg Snider

1.7k citations
30 papers · 1.3k · h-index 15

Impact in

Papers in

Greg Snider

29 papers receiving 1.3k citations

Peers

Greg Snider
Comparison fields: 5 of 56
  • Cellular and Molecular Neuroscience 387
  • Hardware and Architecture 149
  • Electrical and Electronic Engineering 1.1k
  • Cognitive Neuroscience 226
  • Computational Theory and Mathematics 127
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Mika Laiho Finland
Kyoung-Rok Cho South Korea
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Hossam A. H. Fahmy Egypt
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Citations per field
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Citations per year

Countries citing papers authored by Greg Snider

Since Specialization
Citations

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

Fields of papers citing papers by Greg Snider

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008266
2 2007232
3 2008204
4 2004156
5 201174
6 200164
7 199562
8 200256
9 200731
10 201030
11 200230
12 200125
13 200622
14 200520
15
Spacewalker: Automated Design Space Exploration for Embedded Computer Systems
200114
16 200612
17 200710
18 19957
19
Measuring the Entropy of Large Software Systems
20017
20 20116

About Greg Snider

Greg Snider is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Hardware and Architecture, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 30 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (11 papers), Neural dynamics and brain function (8 papers), Embedded Systems Design Techniques (6 papers), Advancements in Semiconductor Devices and Circuit Design (6 papers), Parallel Computing and Optimization Techniques (6 papers), Semiconductor materials and devices (5 papers), DNA and Biological Computing (4 papers) and Neuroscience and Neural Engineering (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (387 citations), Hardware and Architecture (149 citations), Electrical and Electronic Engineering (1.1k citations), Cognitive Neuroscience (226 citations) and Computational Theory and Mathematics (127 citations). Greg Snider has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Philip J. Kuekes, R. Stanley Williams, Richard J. Carter, R. G. Beausoleil, Shih-Yuan Wang, Tad Hogg, Rick Amerson, W. Bruce Culbertson, Warren Robinett and Hiroto Yasuura. Their work appears in journals such as IEEE Transactions on Nanotechnology, Nanotechnology, BMC Neuroscience, Genetic Programming and Evolvable Machines and Computer.

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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