Arun Das

1.7k citations
31 papers · 369 · h-index 11

Impact in

Papers in

Arun Das

28 papers receiving 353 citations

Peers

Arun Das
Comparison fields: 5 of 81
  • Geology 85
  • Computer Vision and Pattern Recognition 167
  • Aerospace Engineering 165
  • Health Informatics 8
  • Environmental Engineering 64
Replace Zizhao Wu with:
Zizhao Wu China
Andrei Bursuc France
Abd El Rahman Shabayek Luxembourg
Martin Humenberger Austria
Jay Karhade India
Ue-Hwan Kim South Korea
Xun Xu Singapore
Giovanni Pintore Italy
Pengcheng Shi China
Arun Das relative to Zizhao Wu China Zizhao Wu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Arun Das

Since Specialization
Citations

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

Fields of papers citing papers by Arun Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201457
2 201857
3 201243
4 201333
5 201324
6 202119
7 201417
8 202314
9 201913
10 201511
11 201710
12 20148
13 20188
14 20168
15 20237
16 20217
17 20176
18 20225
19 20184
20 20184

About Arun Das

Arun Das is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Cognitive Neuroscience, Signal Processing and Artificial Intelligence, having authored 31 papers that have together received 369 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (13 papers), Advanced Vision and Imaging (4 papers), 3D Surveying and Cultural Heritage (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Robotic Path Planning Algorithms (3 papers), Neurobiology of Language and Bilingualism (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Geology (85 citations), Computer Vision and Pattern Recognition (167 citations), Aerospace Engineering (165 citations), Health Informatics (8 citations) and Environmental Engineering (64 citations). Arun Das has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Steven L. Waslander, Paul Rad, Joseph R. Martel, Kim‐Kwang Raymond Choo, John Zelek, Amarie Carnett, Christian Scharfenberger, Leslie Neely, David A. Clausi and Peyman Najafirad. Their work appears in journals such as Journal of Field Robotics, Traffic Injury Prevention, Frontiers in Neuroscience, Journal of Medical Virology and The International Journal of Robotics Research.

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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