Shah Muhammad Hamdi
- Signal Processing top 5%
- Time Series Analysis and Forecasting 22
- Data Management and Algorithms 7
- Astronomy and Astrophysics top 10%
- Solar and Space Plasma Dynamics 15
- Artificial Intelligence top 10%
- Solar Radiation and Photovoltaics 10
- Anomaly Detection Techniques and Applications 10
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- Currency Recognition and Detection 10
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- Stock Market Forecasting Methods 7
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- Market Dynamics and Volatility 11
- Co-authors
- Soukaïna Filali BoubrahimiRafal A. AngrykDustin KemptonRuizhe MaBerkay AydinMichael A. SchuhManolis K. GeorgoulisSunitha Basodi
- Journals
- Water Resources Research (1 paper)The Astrophysical Journal Supplement Series (5 papers)Remote Sensing (1 paper)
- Partner nations
- United StatesSouth KoreaGreece
In The Last Decade
Shah Muhammad Hamdi
51 papers receiving 338 citations
Peers
Comparison fields: 5 of 68
- Signal Processing 112
- Astronomy and Astrophysics 97
- Artificial Intelligence 172
- Computer Vision and Pattern Recognition 99
- Management Science and Operations Research 50
Countries citing papers authored by Shah Muhammad Hamdi
This map shows the geographic impact of Shah Muhammad Hamdi'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 Shah Muhammad Hamdi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shah Muhammad Hamdi more than expected).
Fields of papers citing papers by Shah Muhammad Hamdi
This network shows the impact of papers produced by Shah Muhammad Hamdi. 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 Shah Muhammad Hamdi. The network helps show where Shah Muhammad Hamdi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shah Muhammad Hamdi, 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 | 1 | |
| 4 | 2025 | 3 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 12 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 5 | |
| 9 | 2024 | 10 | |
| 10 | 2024 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2023 | 5 | |
| 15 | 2023 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2023 | 1 | |
| 18 | 2020 | 95 | |
| 19 | Spatiotemporal Frequent Pattern Discovery from Solar Event Metadata | 2016 | 1 |
| 20 | 2016 | 6 |
About Shah Muhammad Hamdi
Shah Muhammad Hamdi is a scholar working on Computational Mathematics, Signal Processing and Artificial Intelligence, having authored 59 papers that have together received 353 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (22 papers), Solar and Space Plasma Dynamics (15 papers), Market Dynamics and Volatility (11 papers), Solar Radiation and Photovoltaics (10 papers), Anomaly Detection Techniques and Applications (10 papers), Currency Recognition and Detection (10 papers), Stock Market Forecasting Methods (7 papers) and Data Management and Algorithms (7 papers). The work is most often cited by research in Signal Processing (112 citations), Astronomy and Astrophysics (97 citations) and Artificial Intelligence (172 citations). Shah Muhammad Hamdi has collaborated with scholars based in United States, South Korea and Greece. Frequent co-authors include Soukaïna Filali Boubrahimi, Rafal A. Angryk, Dustin Kempton, Ruizhe Ma, Berkay Aydin, Michael A. Schuh, Manolis K. Georgoulis, Sunitha Basodi, Ayman Nassar and P. C. H. Martens. Their work appears in journals such as Water Resources Research, The Astrophysical Journal Supplement Series and Remote Sensing.
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.