Jeff LaCoss
- Hardware and Architecture top 5%
- Electrical and Electronic Engineering
- Computer Networks and Communications top 5%
- Cognitive Neuroscience top 10%
- Cellular and Molecular Neuroscience top 10%
- Co-authors
- John GranackiJeff DraperJaewook ShinJack WillsMary HallJacqueline ChameVasilis Z. MarmarelisTheodore W. Berger
- Topics
- Neuroscience and Neural Engineering (9 papers)Advanced Memory and Neural Computing (8 papers)Analog and Mixed-Signal Circuit Design (4 papers)
- Cited by
- Hardware and ArchitectureComputer Networks and CommunicationsCellular and Molecular Neuroscience
- Journals
- IEEE Transactions on Neural Systems and Rehabilitation EngineeringJournal of Neuroscience MethodsConference proceedings
- Partner nations
- United States
In The Last Decade
Jeff LaCoss
12 papers receiving 439 citations
Peers
Comparison fields: 5 of 41
- Hardware and Architecture 228
- Electrical and Electronic Engineering 204
- Computer Networks and Communications 204
- Cognitive Neuroscience 130
- Cellular and Molecular Neuroscience 127
Countries citing papers authored by Jeff LaCoss
This map shows the geographic impact of Jeff LaCoss'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 Jeff LaCoss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff LaCoss more than expected).
Fields of papers citing papers by Jeff LaCoss
This network shows the impact of papers produced by Jeff LaCoss. 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 Jeff LaCoss. The network helps show where Jeff LaCoss may publish in the future.
Co-authorship network of co-authors of Jeff LaCoss
This figure shows the co-authorship network connecting the top 25 collaborators of Jeff LaCoss. A scholar is included among the top collaborators of Jeff LaCoss based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jeff LaCoss. Jeff LaCoss is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 104 | |
| 2 | 12 | |
| 3 | 4 | |
| 4 | 8 | |
| 5 | 20 | |
| 6 | 12 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 10 | |
| 10 | 150 | |
| 11 | 2 | |
| 12 | 135 |
About Jeff LaCoss
Jeff LaCoss is a scholar working on Cellular and Molecular Neuroscience, Hardware and Architecture and Cognitive Neuroscience, having authored 12 papers that have together received 462 indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (9 papers), Advanced Memory and Neural Computing (8 papers) and Analog and Mixed-Signal Circuit Design (4 papers). The work is most often cited by research in Hardware and Architecture (228 citations), Computer Networks and Communications (204 citations) and Cellular and Molecular Neuroscience (127 citations). Jeff LaCoss has collaborated with scholars based in United States. Frequent co-authors include John Granacki, Jeff Draper, Jaewook Shin, Jack Wills, Mary Hall, Jacqueline Chame, Vasilis Z. Marmarelis, Theodore W. Berger, Tim Barrett and Craig S. Steele. Their work appears in journals such as IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal of Neuroscience Methods and Conference proceedings.
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.