A. Sutherland

595 citations
15 papers · 315 · h-index 7

Impact in

    • Machine Learning and Data Classification
    • Imbalanced Data Classification Techniques
    • Neural Networks and Applications
    • Data Stream Mining Techniques
    • Evolutionary Algorithms and Applications
    • Machine Learning and Algorithms
    • Face and Expression Recognition

Papers in

A. Sutherland

14 papers receiving 284 citations

Peers

A. Sutherland
Comparison fields: 5 of 84
  • Artificial Intelligence 170
  • Computer Vision and Pattern Recognition 50
  • Health Information Management 9
  • Information Systems 48
  • Computational Theory and Mathematics 24
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A. Sutherland relative to Majid Alkhambashi Egypt Majid Alkhambashi's profile →
Citations per field
00.5×10×15×19×
Majid Alkhambashi · 1×
Citations per year

Countries citing papers authored by A. Sutherland

Since Specialization
Citations

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

Fields of papers citing papers by A. Sutherland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 1995243
2 199414
3 202313
4 196311
5 20089
6 19607
7 19606
8 20192
9 19942
10 20082
11 19932
12 20192
13 20211
14 20231
15 20080

About A. Sutherland

A. Sutherland is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Nuclear and High Energy Physics, Artificial Intelligence and Aerospace Engineering, having authored 15 papers that have together received 315 indexed citations. Recurring topics across this work include Laser-Plasma Interactions and Diagnostics (5 papers), Neural Networks and Applications (4 papers), Particle accelerators and beam dynamics (4 papers), Particle Accelerators and Free-Electron Lasers (3 papers), Electrical Fault Detection and Protection (3 papers), Gyrotron and Vacuum Electronics Research (3 papers), Data Mining Algorithms and Applications (2 papers) and Non-Destructive Testing Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (170 citations), Computer Vision and Pattern Recognition (50 citations), Health Information Management (9 citations), Information Systems (48 citations) and Computational Theory and Mathematics (24 citations). A. Sutherland has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Ross D. King, Cheng Feng, Keith Brown, David Flynn, Chaitanya Desai, Marc P. Y. Desmulliez, Peter Williams, M. Litos, B.M. Alotaibi and T. Heinemann. Their work appears in journals such as Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Physical Review Research, Nature Communications, Applied Artificial Intelligence and Physical Review Accelerators and Beams.

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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