A. Sutherland

585 citations
11 papers · 246 indexed · h-index 5

Impact in

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

Papers in

A. Sutherland

10 papers receiving 220 citations

Peers

A. Sutherland
Comparison fields: 5 of 82
  • Artificial Intelligence 134
  • Computer Vision and Pattern Recognition 42
  • Health Information Management 8
  • Information Systems 33
  • Nuclear and High Energy Physics 15
Replace Dong Zheng with:
Dong Zheng China
Xu Yang China
Majid Alkhambashi Egypt
Daniel Oliveira Brazil
Sean Blanchard United States
Laércio Lima Pilla Brazil
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Lazaros Papadopoulos Greece
A. Sutherland relative to Dong Zheng China Dong Zheng's profile →
Citations per field
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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

11 of 11 papers shown
#Work
1 1995206
2 202312
3 20088
4 19607
5 19605
6 20192
7 20192
8 20082
9 20231
10 20211
11 20080

About A. Sutherland

A. Sutherland is a scholar working on Nuclear and High Energy Physics, Radiation, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Aerospace Engineering, having authored 11 papers that have together received 246 indexed citations. Recurring topics across this work include Laser-Plasma Interactions and Diagnostics (5 papers), Electrical Fault Detection and Protection (3 papers), Particle Accelerators and Free-Electron Lasers (3 papers), Particle accelerators and beam dynamics (3 papers), Advanced X-ray Imaging Techniques (2 papers), Gyrotron and Vacuum Electronics Research (2 papers), Non-Destructive Testing Techniques (2 papers) and Concrete Corrosion and Durability (1 paper). The work is most often cited by research in Artificial Intelligence (134 citations), Computer Vision and Pattern Recognition (42 citations), Health Information Management (8 citations), Information Systems (33 citations) and Nuclear and High Energy Physics (15 citations). A. Sutherland has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Cheng Feng, Ross D. King, Marc P. Y. Desmulliez, T. Raubenheimer, J. B. Rosenzweig, T. Heinemann, B. Hidding, Brian McNeil, E. Hemsing and A. F. Habib. Their work appears in journals such as Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Nature Communications, Applied Artificial Intelligence, Physical Review Research 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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