David Boland

46 papers receiving 392 citations

Peers

David Boland
Comparison fields: 5 of 54
  • Hardware and Architecture 124
  • Computational Theory and Mathematics 104
  • Computer Vision and Pattern Recognition 81
  • Electrical and Electronic Engineering 208
  • Artificial Intelligence 111
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Van‐Phuc Hoang Vietnam
Martin Langhammer United Kingdom
Stefan Mach Switzerland
Eugene John United States
José T. de Sousa Portugal
Pong P. Chu United States
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Citations per year

Countries citing papers authored by David Boland

Since Specialization
Citations

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

Fields of papers citing papers by David Boland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201945
2 201839
3 200825
4 202022
5 201719
6 201917
7 201116
8 201316
9 201716
10 201014
11 201813
12 201413
13 201812
14 201412
15 201210
16 201110
17 201910
18 20208
19 20238
20 20187

About David Boland

David Boland is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture, Computational Theory and Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 404 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (16 papers), Low-power high-performance VLSI design (14 papers), Parallel Computing and Optimization Techniques (11 papers), VLSI and Analog Circuit Testing (7 papers), Advanced Neural Network Applications (6 papers), Wireless Signal Modulation Classification (4 papers), Neural Networks and Applications (4 papers) and Blind Source Separation Techniques (4 papers). The work is most often cited by research in Hardware and Architecture (124 citations), Computational Theory and Mathematics (104 citations), Computer Vision and Pattern Recognition (81 citations), Electrical and Electronic Engineering (208 citations) and Artificial Intelligence (111 citations). David Boland has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include George A. Constantinides, Philip H. W. Leong, Duncan J. M. Moss, Peter Zipf, Martin Kumm, Lindsay Kleeman, Tom Drummond, Ryan Kastner, Edward Stott and Bill Corcoran. Their work appears in journals such as ACM Transactions on Reconfigurable Technology and Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Optics Express and IEEE Transactions on Services Computing.

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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