Supreet Singh
Impact in
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- Advanced Combustion Engine Technologies
- Artificial Intelligence top 10%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
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- Metaheuristic Optimization Algorithms Research 16
- Evolutionary Algorithms and Applications 7
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- Advanced Multi-Objective Optimization Algorithms 8
- Co-authors
- Urvinder Singh (15 shared papers)Rohit Salgotra (10 shared papers)Nitin Mittal (11 shared papers)Gurdeep Singh (3 shared papers)Atul Verma (1 shared paper)Amir H. Gandomi (5 shared papers)Shankar Prakriya (1 shared paper)Surbhi Sharma (2 shared papers)
In The Last Decade
Supreet Singh
27 papers receiving 305 citations
Peers
Comparison fields: 5 of 50
- Fluid Flow and Transfer Processes 26
- Artificial Intelligence 124
- Computational Theory and Mathematics 45
- Computer Networks and Communications 61
- Industrial and Manufacturing Engineering 23
Countries citing papers authored by Supreet Singh
This map shows the geographic impact of Supreet Singh'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 Supreet Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Supreet Singh more than expected).
Fields of papers citing papers by Supreet Singh
This network shows the impact of papers produced by Supreet Singh. 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 Supreet Singh. The network helps show where Supreet Singh may publish in the future.
Co-authors
The 25 scholars most cited alongside Supreet Singh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 73 | |
| 2 | 2021 | 36 | |
| 3 | 2021 | 32 | |
| 4 | 2017 | 26 | |
| 5 | 2020 | 24 | |
| 6 | 2022 | 21 | |
| 7 | 2022 | 16 | |
| 8 | 2021 | 12 | |
| 9 | 2017 | 10 | |
| 10 | 2024 | 9 | |
| 11 | 2023 | 7 | |
| 12 | 2022 | 6 | |
| 13 | 2023 | 5 | |
| 14 | 2025 | 4 | |
| 15 | 2021 | 4 | |
| 16 | 2017 | 4 | |
| 17 | 2022 | 3 | |
| 18 | 2023 | 3 | |
| 19 | 2016 | 3 | |
| 20 | 2024 | 2 |
About Supreet Singh
Supreet Singh is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Electrical and Electronic Engineering and Biomedical Engineering, having authored 29 papers that have together received 309 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (16 papers), Advanced Multi-Objective Optimization Algorithms (8 papers), Evolutionary Algorithms and Applications (7 papers), Advanced MIMO Systems Optimization (3 papers), Energy Efficient Wireless Sensor Networks (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Medical Image Segmentation Techniques (2 papers) and Full-Duplex Wireless Communications (2 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (26 citations), Artificial Intelligence (124 citations), Computational Theory and Mathematics (45 citations), Computer Networks and Communications (61 citations) and Industrial and Manufacturing Engineering (23 citations). Supreet Singh has collaborated with scholars based in India, Australia and Ethiopia. Frequent co-authors include Urvinder Singh, Rohit Salgotra, Nitin Mittal, Gurdeep Singh, Atul Verma, Amir H. Gandomi, Shankar Prakriya, Surbhi Sharma, Bhupinder Singh and Seyedali Mirjalili. Their work appears in journals such as Expert Systems with Applications, Scientific Reports, IEEE Communications Letters, Computer Networks and Computers & Industrial 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.