Muhammad Nabeel Asghar
- Environmental Engineering top 5%
- Hydrological Forecasting Using AI 3
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- Air Quality and Health Impacts 2
- Automotive Engineering top 10%
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- Network Security and Intrusion Detection 2
- Transportation top 10%
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- Advanced Image and Video Retrieval Techniques 3
- Video Analysis and Summarization 2
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- Embedded Systems Design Techniques 2
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- COVID-19 diagnosis using AI 2
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- Machine Learning and Data Classification 2
- Co-authors
- Munam Ali ShahCarsten MapleSaif ul IslamAbid KhanHoubing SongRahat IqbalHassaan MalikMuhammad Faheem
- Partner nations
- PakistanUnited KingdomSaudi Arabia
In The Last Decade
Muhammad Nabeel Asghar
25 papers receiving 450 citations
Peers
Comparison fields: 5 of 77
- Environmental Engineering 165
- Health, Toxicology and Mutagenesis 111
- Automotive Engineering 73
- Computer Networks and Communications 133
- Transportation 28
Countries citing papers authored by Muhammad Nabeel Asghar
This map shows the geographic impact of Muhammad Nabeel Asghar'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 Nabeel Asghar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Nabeel Asghar more than expected).
Fields of papers citing papers by Muhammad Nabeel Asghar
This network shows the impact of papers produced by Muhammad Nabeel Asghar. 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 Nabeel Asghar. The network helps show where Muhammad Nabeel Asghar may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Muhammad Nabeel Asghar, 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 | 2024 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 47 | |
| 8 | 2022 | 1 | |
| 9 | 2022 | 29 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 3 | |
| 12 | 2022 | 24 | |
| 13 | 2021 | 34 | |
| 14 | 2021 | 11 | |
| 15 | 2020 | 8 | |
| 16 | 2020 | 23 | |
| 17 | 2019 | 27 | |
| 18 | 2017 | 53 | |
| 19 | 2017 | 1 | |
| 20 | A framework for feature based dynamic intravideo indexing | 2013 | 2 |
About Muhammad Nabeel Asghar
Muhammad Nabeel Asghar is a scholar working on Hardware and Architecture, Computer Networks and Communications and Signal Processing, having authored 28 papers that have together received 479 indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Air Quality and Health Impacts (2 papers), Video Analysis and Summarization (2 papers), Network Security and Intrusion Detection (2 papers), Embedded Systems Design Techniques (2 papers), COVID-19 diagnosis using AI (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Environmental Engineering (165 citations), Health, Toxicology and Mutagenesis (111 citations) and Automotive Engineering (73 citations). Muhammad Nabeel Asghar has collaborated with scholars based in Pakistan, United Kingdom and Saudi Arabia. Frequent co-authors include Munam Ali Shah, Carsten Maple, Saif ul Islam, Abid Khan, Houbing Song, Rahat Iqbal, Hassaan Malik, Muhammad Faheem, Tayyaba Anees and Ejaz Ahmed. Their work appears in journals such as PLoS ONE, IEEE Access and Sustainability.
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.