Robert Gray

1.7k citations
30 papers · 1.1k indexed · 1 hit paper · h-index 16

Robert Gray

30 papers receiving 1.1k citations

Hit Papers

NiftyNet: a deep-learning platform for medical imaging3632018202620202023100200300

Peers

Robert Gray
Comparison fields: 5 of 132
  • Health Informatics 39
  • Geophysics 170
  • Neurology 99
  • Radiology, Nuclear Medicine and Imaging 252
  • Computer Vision and Pattern Recognition 175
Replace Yanbo Zhang with:
Yanbo Zhang China
Yuan Xu China
Qingsong Yang China
Dean Ta China
Marcus Stoffel Germany
Yu Dai China
Minhua Lu China
Xiaodong Guo China
Manning Wang China
Alex Hartov United States
Robert Gray relative to Yanbo Zhang China Yanbo Zhang's profile →
Citations per field
00.5×5.8×
Yanbo Zhang · 1×
Citations per year

Countries citing papers authored by Robert Gray

Since Specialization
Citations

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

Fields of papers citing papers by Robert Gray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202412
2 20239
3 202212
4 202220
5 20229
6 202299
7 202132
8 20215
9 202118
10
NiftyNet: a deep-learning platform for medical imagingbreakdown →
2018363
11 201814
12 201769
13 20135
14 20132
15 20131
16 201211
17 1984101
18 198428
19 197433
20 196613

About Robert Gray

Robert Gray is a scholar working on Structural Biology, Geophysics and Neurology, having authored 30 papers that have together received 1.1k indexed citations. Recurring topics across this work include earthquake and tectonic studies (7 papers), Geological and Geochemical Analysis (6 papers), High-pressure geophysics and materials (6 papers), Innovative concrete reinforcement materials (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Mechanical Behavior of Composites (3 papers), Structural Behavior of Reinforced Concrete (3 papers) and Fiber-reinforced polymer composites (2 papers). The work is most often cited by research in Health Informatics (39 citations), Geophysics (170 citations) and Neurology (99 citations). Robert Gray has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include R. N. Pysklywec, Parashkev Nachev, M. Jorge Cardoso, Sébastien Ourselin, Guotai Wang, Dzhoshkun I. Shakir, Yipeng Hu, Marc Modat, Lucas Fidon and T. Whyntie. Their work appears in journals such as Geophysical Research Letters, Journal of Geophysical Research Atmospheres, Brain Communications, Cement and Concrete Research and SAE technical papers on CD-ROM/SAE technical paper series.

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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