Muhammad Muneeb
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
Papers in
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- Energy Load and Power Forecasting 5
-
- Blockchain Technology Applications and Security 6
- Co-authors
- Aneela Zameer (4 shared papers)Farah Shahid (3 shared papers)Irfan Ul Haq (7 shared papers)Muhammad Irfan (1 shared paper)Omair Shafiq (3 shared papers)Andreas Henschel (7 shared papers)Sikander M. Mirza (1 shared paper)Kwangman Ko (2 shared papers)
- Journals
- IEEE Access (5 papers)PLoS ONE (3 papers)BMC Bioinformatics (3 papers)Applied Sciences (1 paper)Chaos Solitons & Fractals (1 paper)
- Partner nations
- PakistanUnited Arab EmiratesSouth Korea
In The Last Decade
Muhammad Muneeb
29 papers receiving 1.2k citations
Muhammad Muneeb's Hit Papers
Peers
Comparison fields: 5 of 132
- Modeling and Simulation 147
- Energy Engineering and Power Technology 39
- Artificial Intelligence 381
- Management Science and Operations Research 118
- Information Systems 190
Countries citing papers authored by Muhammad Muneeb
This map shows the geographic impact of Muhammad Muneeb'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 Muhammad Muneeb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Muneeb more than expected).
Fields of papers citing papers by Muhammad Muneeb
This network shows the impact of papers produced by Muhammad Muneeb. 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 Muhammad Muneeb. The network helps show where Muhammad Muneeb may publish in the future.
Co-authors
The 25 scholars most cited alongside Muhammad Muneeb, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM Hit paper breakdown → | 2020 | 503 |
| 2 | A novel genetic LSTM model for wind power forecast Hit paper breakdown → | 2021 | 378 |
| 3 | 2018 | 95 | |
| 4 | 2021 | 40 | |
| 5 | 2019 | 39 | |
| 6 | 2023 | 34 | |
| 7 | 2023 | 31 | |
| 8 | 2021 | 25 | |
| 9 | 2021 | 20 | |
| 10 | 2021 | 12 | |
| 11 | 2024 | 11 | |
| 12 | 2021 | 11 | |
| 13 | 2023 | 9 | |
| 14 | 2022 | 7 | |
| 15 | 2022 | 6 | |
| 16 | 2022 | 5 | |
| 17 | 2022 | 5 | |
| 18 | 2021 | 5 | |
| 19 | 2023 | 4 | |
| 20 | 2021 | 4 |
About Muhammad Muneeb
Muhammad Muneeb is a scholar working on Electrical and Electronic Engineering, Information Systems, Computer Networks and Communications, Molecular Biology and Artificial Intelligence, having authored 30 papers that have together received 1.3k indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (6 papers), Energy Load and Power Forecasting (5 papers), IoT and Edge/Fog Computing (4 papers), Gene expression and cancer classification (3 papers), Human Mobility and Location-Based Analysis (3 papers), Solar Radiation and Photovoltaics (3 papers), Traffic Prediction and Management Techniques (3 papers) and Transportation Planning and Optimization (2 papers). The work is most often cited by research in Modeling and Simulation (147 citations), Energy Engineering and Power Technology (39 citations), Artificial Intelligence (381 citations), Management Science and Operations Research (118 citations) and Information Systems (190 citations). Muhammad Muneeb has collaborated with scholars based in Pakistan, United Arab Emirates and South Korea. Frequent co-authors include Aneela Zameer, Farah Shahid, Irfan Ul Haq, Muhammad Irfan, Omair Shafiq, Andreas Henschel, Sikander M. Mirza, Kwangman Ko, Young-Hoon Park and Rizwan Khan. Their work appears in journals such as IEEE Access, PLoS ONE, BMC Bioinformatics, Applied Sciences and Chaos Solitons & Fractals.
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.