Travis DeWolf

1.8k citations
9 papers · 1.0k · 1 hit paper · h-index 8

Impact in

Papers in

Travis DeWolf

9 papers receiving 990 citations

Travis DeWolf's Hit Papers

A Large-Scale Model of the Functioning Brain 2012 · 560 citations
5600+4+9Years since publication100200300400500

Peers

Travis DeWolf
Comparison fields: 5 of 78
  • Cognitive Neuroscience 642
  • Cellular and Molecular Neuroscience 225
  • Artificial Intelligence 365
  • Electrical and Electronic Engineering 583
  • Social Psychology 49
Replace Xuan Choo with:
Xuan Choo Canada
Trevor Bekolay Canada
Yichuan Tang United States
Yulia Sandamirskaya Switzerland
Bernd Porr United Kingdom
Fopefolu Folowosele United States
K.M. Hynna United States
Andreas Knoblauch Germany
Jeffrey L. McKinstry United States
Philipp Häfliger Norway
Travis DeWolf relative to Xuan Choo Canada Xuan Choo's profile →
Citations per field
00.5×1.5×
Xuan Choo · 1×
Citations per year

Countries citing papers authored by Travis DeWolf

Since Specialization
Citations

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

Fields of papers citing papers by Travis DeWolf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Travis DeWolf, 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 Travis DeWolf Line = papers co-authored together Travis DeWolf links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
A Large-Scale Model of the Functioning Brain
Hit paper breakdown →
2012560
2 2014299
3 202054
4 201653
5 201120
6 202113
7 201511
8 202311
9 20226

About Travis DeWolf

Travis DeWolf is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Artificial Intelligence and Social Psychology, having authored 9 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (5 papers), Advanced Memory and Neural Computing (5 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Functional Brain Connectivity Studies (2 papers), Neural Networks and Applications (2 papers), Motor Control and Adaptation (2 papers), Genetic Neurodegenerative Diseases (1 paper) and Muscle activation and electromyography studies (1 paper). The work is most often cited by research in Cognitive Neuroscience (642 citations), Cellular and Molecular Neuroscience (225 citations), Artificial Intelligence (365 citations), Electrical and Electronic Engineering (583 citations) and Social Psychology (49 citations). Travis DeWolf has collaborated with scholars based in Canada, United States and South Africa. Frequent co-authors include Chris Eliasmith, Terrence C. Stewart, Daniel Rasmussen, Trevor Bekolay, Xuan Choo, Yichuan Tang, Eric Hunsberger, James Bergstra, Aaron R. Voelker and Jean-Jacques Slotine. Their work appears in journals such as Frontiers in Neuroinformatics, Science, Proceedings of the Royal Society B Biological Sciences, Journal of Neural Engineering and Patterns.

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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