Subhrajit Roy

1.4k citations
23 papers · 1k · h-index 13

Impact in

Papers in

Subhrajit Roy

22 papers receiving 995 citations

Peers

Subhrajit Roy
Comparison fields: 5 of 76
  • Health Informatics 66
  • Cognitive Neuroscience 539
  • Psychiatry and Mental health 128
  • Artificial Intelligence 203
  • Computer Vision and Pattern Recognition 68
Replace Manob Jyoti Saikia with:
Manob Jyoti Saikia United States
Pedro F. da Costa United Kingdom
Delaram Sadeghi Australia
Yingying Zhu United States
Κostas Μ. Tsiouris Greece
Haitao Gan China
Lan Wei Ireland
Jiannan Zheng China
Mousa Shamsi Iran
Noushath Shaffi Oman
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Citations per field
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Manob Jyoti Saikia · 1×
Citations per year

Countries citing papers authored by Subhrajit Roy

Since Specialization
Citations

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

Fields of papers citing papers by Subhrajit Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017237
2 2019154
3 2021110
4 201187
5 202074
6 202062
7 202254
8 201846
9 201240
10 202233
11
Privacy Preserving Human Fall Detection using Video Data
201927
12 201616
13 202116
14 202112
15 201111
16 201211
17
Machine Learning for Seizure Type Classification: Setting the benchmark.
201911
18 20127
19
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All
20205
20 20142

About Subhrajit Roy

Subhrajit Roy is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Health Informatics, Psychiatry and Mental health and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 1k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (8 papers), Metaheuristic Optimization Algorithms Research (4 papers), Machine Learning in Healthcare (3 papers), Antenna Design and Optimization (2 papers), Epilepsy research and treatment (2 papers), Advanced Memory and Neural Computing (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Context-Aware Activity Recognition Systems (2 papers). The work is most often cited by research in Health Informatics (66 citations), Cognitive Neuroscience (539 citations), Psychiatry and Mental health (128 citations), Artificial Intelligence (203 citations) and Computer Vision and Pattern Recognition (68 citations). Subhrajit Roy has collaborated with scholars based in Australia, India and United States. Frequent co-authors include Stefan Harrer, Isabell Kiral-Kornek, Umar Asif, Jianbin Tang, Swagatam Das, Saurav Ghosh, Diana Mincu, Benjamin S. Mashford, Ponnuthurai Nagaratnam Suganthan and Terence John O'Brien. Their work appears in journals such as EBioMedicine, Journal of the American Medical Informatics Association, Applied Soft Computing, Epilepsia and Scientific Reports.

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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