Arjuna Madanayake
- Signal Processing top 1%
- Digital Filter Design and Implementation 66
- Speech and Audio Processing 26
- Aerospace Engineering top 0.5%
- Antenna Design and Optimization 55
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- Microwave Engineering and Waveguides 72
- Radio Frequency Integrated Circuit Design 46
- Millimeter-Wave Propagation and Modeling 36
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- Advanced Data Compression Techniques 25
- Media Technology top 2%
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- Advanced Adaptive Filtering Techniques 58
- Co-authors
- Soumyajit MandalTheodore S. RappaportGeorgios C. TrichopoulosAhmed AlkhateebShihao JuYunchou XingOjas KanhereL.T. Bruton
- Journals
- SHILAP Revista de lepidopterología (1 paper)Applied Physics Letters (1 paper)Scientific Reports (1 paper)
- Partner nations
- United StatesCanadaBrazil
In The Last Decade
Arjuna Madanayake
245 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Signal Processing 716
- Aerospace Engineering 1.2k
- Electrical and Electronic Engineering 2.6k
- Computer Vision and Pattern Recognition 532
- Media Technology 179
Countries citing papers authored by Arjuna Madanayake
This map shows the geographic impact of Arjuna Madanayake'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 Arjuna Madanayake with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arjuna Madanayake more than expected).
Fields of papers citing papers by Arjuna Madanayake
This network shows the impact of papers produced by Arjuna Madanayake. 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 Arjuna Madanayake. The network helps show where Arjuna Madanayake may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Arjuna Madanayake, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 51 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 1 | |
| 10 | 2023 | 2 | |
| 11 | 2023 | 2 | |
| 12 | 2023 | 8 | |
| 13 | 2022 | 0 | |
| 14 | 2022 | 16 | |
| 15 | 2021 | 9 | |
| 16 | 2021 | 1 | |
| 17 | 2021 | 1 | |
| 18 | 2020 | 4 | |
| 19 | 2020 | 2 | |
| 20 | Wireless Communications and Applications Above 100 GHz: Opportunities and Challenges for 6G and Beyondbreakdown → | 2019 | 1574 |
About Arjuna Madanayake
Arjuna Madanayake is a scholar working on Signal Processing, Aerospace Engineering and Computational Mechanics, having authored 263 papers that have together received 3.9k indexed citations. Recurring topics across this work include Microwave Engineering and Waveguides (72 papers), Digital Filter Design and Implementation (66 papers), Advanced Adaptive Filtering Techniques (58 papers), Antenna Design and Optimization (55 papers), Radio Frequency Integrated Circuit Design (46 papers), Millimeter-Wave Propagation and Modeling (36 papers), Speech and Audio Processing (26 papers) and Advanced Data Compression Techniques (25 papers). The work is most often cited by research in Signal Processing (716 citations), Aerospace Engineering (1.2k citations) and Electrical and Electronic Engineering (2.6k citations). Arjuna Madanayake has collaborated with scholars based in United States, Canada and Brazil. Frequent co-authors include Soumyajit Mandal, Theodore S. Rappaport, Georgios C. Trichopoulos, Ahmed Alkhateeb, Shihao Ju, Yunchou Xing, Ojas Kanhere, L.T. Bruton, Renato J. Cintra and Gihan J. Mendis. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Physics Letters 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.