Debabrota Basu

500 citations
17 papers · 216 · h-index 7

Impact in

Papers in

Debabrota Basu

16 papers receiving 209 citations

Peers

Debabrota Basu
Comparison fields: 5 of 51
  • Computer Networks and Communications 83
  • Information Systems 70
  • Artificial Intelligence 90
  • Signal Processing 19
  • Cognitive Neuroscience 31
Replace Wenjie Wang with:
Wenjie Wang China
Roziana Ramli Malaysia
Volodymyr Sokolov Ukraine
Fangyang Shen United States
J Thriveni India
Mohammad Momani Jordan
Konstantinos Κarampidis Greece
Mohamed Abu ElSoud Egypt
Khaled M. Alalayah Saudi Arabia
Amiza Amir Malaysia
Debabrota Basu relative to Wenjie Wang China Wenjie Wang's profile →
Citations per field
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Wenjie Wang · 1×
Citations per year

Countries citing papers authored by Debabrota Basu

Since Specialization
Citations

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

Fields of papers citing papers by Debabrota Basu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201951
2 201550
3 202127
4 201426
5 202113
6 202111
7 201711
8 20216
9 20225
10 20115
11 20143
12 20233
13
Integration of kernel and DCT coefficient fuzzy matching techniques for human face recognition
20022
14 20251
15 20241
16 20141
17
Bandits Corrupted by Nature:Lower Bounds on Regret and Robust Optimistic Algorithms
20240

About Debabrota Basu

Debabrota Basu is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Safety Research and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 216 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (3 papers), Cloud Computing and Resource Management (3 papers), Data Stream Mining Techniques (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Fuzzy Logic and Control Systems (2 papers), Adversarial Robustness in Machine Learning (2 papers), Distributed systems and fault tolerance (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Computer Networks and Communications (83 citations), Information Systems (70 citations), Artificial Intelligence (90 citations), Signal Processing (19 citations) and Cognitive Neuroscience (31 citations). Debabrota Basu has collaborated with scholars based in France, Singapore and United States. Frequent co-authors include D. N. Tibarewala, Saugat Bhattacharyya, Amit Konar, Xiayang Wang, Haibo Chen, Stéphane Bressan, Junxiong Wang, Immanuel Trummer, Kuldeep S. Meel and Subhodip Biswas. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, Robotics and Autonomous Systems, IEEE Transactions on Cybernetics, Proceedings of the VLDB Endowment and Journal of Marine Science and Engineering.

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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