Andrew Starkey

506 citations
41 papers · 300 · h-index 9

Impact in

Papers in

Andrew Starkey

36 papers receiving 288 citations

Peers

Andrew Starkey
Comparison fields: 5 of 100
  • Artificial Intelligence 88
  • Behavioral Neuroscience 9
  • Cellular and Molecular Neuroscience 29
  • Civil and Structural Engineering 35
  • Mechanics of Materials 38
Replace Jong‐Hyun Kim with:
Jong‐Hyun Kim South Korea
Pengcheng Xiao China
Zhongming Liu China
Gabriel Krummenacher Switzerland
Guillermo Iglesias Spain
Sebastián Salazar-Colores Mexico
Zhiya Chen China
Suprijanto Suprijanto Indonesia
Xing Fu China
Jifeng Guo China
Andrew Starkey relative to Jong‐Hyun Kim South Korea Jong‐Hyun Kim's profile →
Citations per field
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Jong‐Hyun Kim · 1×
Citations per year

Countries citing papers authored by Andrew Starkey

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Starkey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201157
2 201948
3
Small signal modelling and stability analysis of multiterminal VSC-HVDC
201125
4 202123
5 200922
6 200617
7 202113
8 201712
9 200311
10 20038
11 20177
12 20206
13 20236
14 20035
15 20234
16 20093
17 20233
18 20153
19 20173
20 20233

About Andrew Starkey

Andrew Starkey is a scholar working on Artificial Intelligence, Civil and Structural Engineering, Mechanics of Materials, Computer Vision and Pattern Recognition and Ocean Engineering, having authored 41 papers that have together received 300 indexed citations. Recurring topics across this work include Geotechnical Engineering and Underground Structures (5 papers), Structural Health Monitoring Techniques (5 papers), Machine Learning and Data Classification (5 papers), Ultrasonics and Acoustic Wave Propagation (5 papers), Face and Expression Recognition (4 papers), Geophysical Methods and Applications (4 papers), Topic Modeling (4 papers) and Imbalanced Data Classification Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (88 citations), Behavioral Neuroscience (9 citations), Cellular and Molecular Neuroscience (29 citations), Civil and Structural Engineering (35 citations) and Mechanics of Materials (38 citations). Andrew Starkey has collaborated with scholars based in United Kingdom, Malaysia and Nigeria. Frequent co-authors include Azwa Abdul Aziz, Alasdair MacKenzie, Scott Davidson, Albert A. Rodger, Ana Ivanović, Richard D. Neilson, Dragan Jovcic, Annika Herwig, Perry Barrett and John P. Quinn. Their work appears in journals such as IEEE Access, Meccanica, Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description, Geotechnical Testing Journal and IEEE Robotics and Automation Letters.

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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