William Severa

497 citations
31 papers · 273 · h-index 8

Impact in

Papers in

William Severa

26 papers receiving 263 citations

Peers

William Severa
Comparison fields: 5 of 47
  • Artificial Intelligence 148
  • Cognitive Neuroscience 74
  • Electrical and Electronic Engineering 177
  • Cellular and Molecular Neuroscience 40
  • Computer Vision and Pattern Recognition 23
Replace Craig M. Vineyard with:
Craig M. Vineyard United States
Pengsheng Zheng China
Benjamin Scellier Switzerland
Aditya Shukla India
Edouard Giacomin United States
Sanjeev Tannirkulam Chandrasekaran United States
Gregor Lenz France
Peng Qu China
Jianming Cai China
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Citations per field
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Citations per year

Countries citing papers authored by William Severa

Since Specialization
Citations

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

Fields of papers citing papers by William Severa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201969
2 201742
3 202233
4 201915
5 202113
6 201613
7 202012
8 201611
9 20217
10 20116
11 20176
12 20195
13 20195
14 20175
15 20214
16 20194
17 20234
18 20194
19 20233
20 20213

About William Severa

William Severa is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 273 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (25 papers), Ferroelectric and Negative Capacitance Devices (19 papers), Neural Networks and Reservoir Computing (10 papers), Neural dynamics and brain function (8 papers), Neural Networks and Applications (4 papers), Advanced SAR Imaging Techniques (2 papers), Neuroscience and Neuropharmacology Research (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Artificial Intelligence (148 citations), Cognitive Neuroscience (74 citations), Electrical and Electronic Engineering (177 citations), Cellular and Molecular Neuroscience (40 citations) and Computer Vision and Pattern Recognition (23 citations). William Severa has collaborated with scholars based in United States and Spain. Frequent co-authors include James B. Aimone, Craig M. Vineyard, Ojas Parekh, Stephen Verzi, Conrad D. James, Kristofor D. Carlson, Cynthia A. Phillips, Ali Pınar, Nadine E. Miner and Jonathan A. Cox. Their work appears in journals such as Scientific Reports, Neural Computation, Nature Machine Intelligence, Journal of Combinatorial Theory Series A 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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