Bill Kay
Impact in
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- CCD and CMOS Imaging Sensors
- Artificial Intelligence top 5%
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
Papers in
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- Limits and Structures in Graph Theory 3
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- Graph Labeling and Dimension Problems 3
- Advanced Graph Theory Research 3
- Co-authors
- Catherine D. SchumanPrasanna DateMaryam ParsaShruti KulkarniJ. Parker MitchellKathleen E. HamiltonThomas E. PotokRobert M. Patton
- Journals
- The Electronic Journal of Combinatorics (2 papers)Discrete Mathematics (2 papers)Scientific Reports (1 paper)Nature Computational Science (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Bill Kay
23 papers receiving 787 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Electrical and Electronic Engineering 643
- Artificial Intelligence 333
- Cellular and Molecular Neuroscience 166
- Cognitive Neuroscience 162
- Discrete Mathematics and Combinatorics 18
Countries citing papers authored by Bill Kay
This map shows the geographic impact of Bill Kay'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 Bill Kay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bill Kay more than expected).
Fields of papers citing papers by Bill Kay
This network shows the impact of papers produced by Bill Kay. 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 Bill Kay. The network helps show where Bill Kay may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bill Kay, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2024 | 5 | |
| 3 | 2024 | 15 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 0 | |
| 6 | 2022 | 33 | |
| 7 | Opportunities for neuromorphic computing algorithms and applications Hit paper breakdown → | 2022 | 615 |
| 8 | 2022 | 0 | |
| 9 | 2022 | 11 | |
| 10 | 2022 | 0 | |
| 11 | 2021 | 9 | |
| 12 | 2021 | 6 | |
| 13 | 2020 | 20 | |
| 14 | 2020 | 4 | |
| 15 | 2020 | 23 | |
| 16 | 2017 | 12 | |
| 17 | 2016 | 9 | |
| 18 | 2013 | 0 | |
| 19 | Contributions to the theory of de Bruijn cycles | 2013 | 0 |
| 20 | 2010 | 6 |
About Bill Kay
Bill Kay is a scholar working on Discrete Mathematics and Combinatorics, Computational Theory and Mathematics, Statistical and Nonlinear Physics, Artificial Intelligence and Electrical and Electronic Engineering, having authored 29 papers that have together received 812 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (9 papers), Ferroelectric and Negative Capacitance Devices (8 papers), Neural Networks and Reservoir Computing (6 papers), Complex Network Analysis Techniques (4 papers), Graph Labeling and Dimension Problems (3 papers), graph theory and CDMA systems (3 papers), Advanced Graph Theory Research (3 papers) and Limits and Structures in Graph Theory (3 papers). The work is most often cited by research in Electrical and Electronic Engineering (643 citations), Artificial Intelligence (333 citations), Cellular and Molecular Neuroscience (166 citations), Cognitive Neuroscience (162 citations) and Discrete Mathematics and Combinatorics (18 citations). Bill Kay has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Catherine D. Schuman, Prasanna Date, Maryam Parsa, Shruti Kulkarni, J. Parker Mitchell, Kathleen E. Hamilton, Thomas E. Potok, Robert M. Patton, Greg Brockman and J. Darby Smith. Their work appears in journals such as The Electronic Journal of Combinatorics, Discrete Mathematics, Scientific Reports, Nature Computational Science and PLoS ONE.
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.