Abhijit Sinha

923 citations
51 papers · 702 indexed · h-index 13

Abhijit Sinha

49 papers receiving 672 citations

Peers

Abhijit Sinha
Comparison fields: 5 of 52
  • Artificial Intelligence 488
  • Aerospace Engineering 281
  • Computer Networks and Communications 204
  • Signal Processing 63
  • Oceanography 67
Replace Aaron D. Lanterman with:
Aaron D. Lanterman United States
Honglei Qin China
Eric Evans United States
Adam Kawalec Poland
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Kevin Gilholm United Kingdom
Vincent C. Vannicola United States
K. Deergha Rao India
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Citations per field
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Aaron D. Lanterman · 1×
Citations per year

Countries citing papers authored by Abhijit Sinha

Since Specialization
Citations

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

Fields of papers citing papers by Abhijit Sinha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20240
3 20232
4 20232
5 20233
6 20231
7 20233
8 20234
9 20225
10 20225
11 20151
12 20147
13 20101
14
An algorithm for multitarget tracking with multiple asynchronous bearings-only sensors
20093
15 20061
16
Effect of higher order non-linearity in frequency variation of self-phase modulation in optical fiber communication
20058
17 200517
18 200511
19 20047
20 20041

About Abhijit Sinha

Abhijit Sinha is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Signal Processing, having authored 51 papers that have together received 702 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (24 papers), Optical Network Technologies (14 papers), Advanced Fiber Laser Technologies (14 papers), Nonlinear Photonic Systems (6 papers), Photonic and Optical Devices (5 papers), Distributed Sensor Networks and Detection Algorithms (5 papers), Nonlinear Waves and Solitons (4 papers) and Radar Systems and Signal Processing (3 papers). The work is most often cited by research in Artificial Intelligence (488 citations), Aerospace Engineering (281 citations) and Computer Networks and Communications (204 citations). Abhijit Sinha has collaborated with scholars based in Canada, India and United States. Frequent co-authors include T. Kirubarajan, Kumaradevan Punithakumar, Ratnasingham Tharmarasa, Yaakov Bar‐Shalom, T. Sathyan, Marcel L. Hernandez, Thomas Lang, Peter Willett, Zhen Wang and T. Kirubarajan. Their work appears in journals such as IEEE Transactions on Aerospace and Electronic Systems, Optical Engineering and IEEE/ACM Transactions on Computational Biology and Bioinformatics.

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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