Rob Shipman

586 citations
27 papers · 459 · h-index 12

Impact in

Papers in

Rob Shipman

26 papers receiving 427 citations

Peers

Rob Shipman
Comparison fields: 5 of 76
  • Artificial Intelligence 209
  • Automotive Engineering 65
  • Genetics 113
  • Computational Theory and Mathematics 40
  • Electrical and Electronic Engineering 133
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Yi Sui China
Germán Obando Colombia
Shouheng Tuo China
Pedro Pereira Portugal
Sung-Wook Park South Korea
Kartick Chandra Mondal India
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Édouard Amouroux France
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Citations per year

Countries citing papers authored by Rob Shipman

Since Specialization
Citations

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

Fields of papers citing papers by Rob Shipman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200181
2 200250
3 199943
4 200038
5 202130
6 202024
7 200023
8 202121
9 200319
10 201318
11 201015
12 202212
13 202011
14
Exon 5 of the p53 gene is a target for deletions in ovarian cancer.
199811
15 202110
16 20199
17 19988
18 20198
19
Towards an electric revolution: a review on vehicle- to-grid, smart charging and user behaviour
20196
20 20016

About Rob Shipman

Rob Shipman is a scholar working on Electrical and Electronic Engineering, Molecular Biology, Automotive Engineering, Artificial Intelligence and Genetics, having authored 27 papers that have together received 459 indexed citations. Recurring topics across this work include Smart Grid Energy Management (8 papers), Electric Vehicles and Infrastructure (7 papers), Evolutionary Algorithms and Applications (5 papers), Evolution and Genetic Dynamics (5 papers), Transportation and Mobility Innovations (4 papers), Advanced Battery Technologies Research (3 papers), Gene Regulatory Network Analysis (3 papers) and Sustainability and Climate Change Governance (2 papers). The work is most often cited by research in Artificial Intelligence (209 citations), Automotive Engineering (65 citations), Genetics (113 citations), Computational Theory and Mathematics (40 citations) and Electrical and Electronic Engineering (133 citations). Rob Shipman has collaborated with scholars based in United Kingdom, Germany and Canada. Frequent co-authors include Mark Shackleton, Marc Ebner, Mark Gillott, Lucélia Rodrigues, Jörg Albert, James Pinchin, Richard A. Watson, Katerina Angelopoulou, Dionyssios Katsaros and Eleftherios P. Diamandis. Their work appears in journals such as Energies, Molecular Diagnosis, Energy Research & Social Science, Drug Metabolism and Disposition and Energy.

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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