Md Nasir
Impact in
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- Emotion and Mood Recognition
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Evolutionary Algorithms and Applications 3
- Speech Recognition and Synthesis 3
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- Emotion and Mood Recognition 7
- Co-authors
- Swagatam Das (6 shared papers)Panayiotis Georgiou (10 shared papers)Soumyadip Sengupta (4 shared papers)Ponnuthurai Nagaratnam Suganthan (3 shared papers)Udit Halder (1 shared paper)Dipankar Maity (1 shared paper)Shubhashis Sengupta (2 shared papers)Athanasios V. Vasilakos (2 shared papers)
- Journals
- PLoS ONE (3 papers)Information Sciences (1 paper)Soft Computing (1 paper)JMIR Public Health and Surveillance (1 paper)Animal Behaviour (1 paper)
- Partner nations
- United StatesIndiaSingapore
In The Last Decade
Md Nasir
30 papers receiving 606 citations
Peers
Comparison fields: 5 of 96
- Experimental and Cognitive Psychology 135
- Computational Theory and Mathematics 135
- Artificial Intelligence 260
- Applied Psychology 36
- Computer Networks and Communications 128
Countries citing papers authored by Md Nasir
This map shows the geographic impact of Md Nasir'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 Md Nasir with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Md Nasir more than expected).
Fields of papers citing papers by Md Nasir
This network shows the impact of papers produced by Md Nasir. 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 Md Nasir. The network helps show where Md Nasir may publish in the future.
Co-authors
The 25 scholars most cited alongside Md Nasir, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 184 | |
| 2 | 2012 | 123 | |
| 3 | 2016 | 98 | |
| 4 | 2011 | 24 | |
| 5 | 2022 | 23 | |
| 6 | 2017 | 20 | |
| 7 | 2015 | 18 | |
| 8 | 2016 | 14 | |
| 9 | 2021 | 13 | |
| 10 | 2017 | 11 | |
| 11 | 2019 | 9 | |
| 12 | 2012 | 8 | |
| 13 | 2015 | 8 | |
| 14 | 2020 | 7 | |
| 15 | 2022 | 7 | |
| 16 | 2022 | 6 | |
| 17 | 2022 | 6 | |
| 18 | 2012 | 6 | |
| 19 | 2016 | 6 | |
| 20 | 2016 | 5 |
About Md Nasir
Md Nasir is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology, Signal Processing, Computational Theory and Mathematics and Social Psychology, having authored 32 papers that have together received 618 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (7 papers), Advanced Multi-Objective Optimization Algorithms (6 papers), Face and Expression Recognition (4 papers), Music and Audio Processing (4 papers), Speech and Audio Processing (4 papers), Face recognition and analysis (4 papers), Evolutionary Algorithms and Applications (3 papers) and Speech Recognition and Synthesis (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (135 citations), Computational Theory and Mathematics (135 citations), Artificial Intelligence (260 citations), Applied Psychology (36 citations) and Computer Networks and Communications (128 citations). Md Nasir has collaborated with scholars based in United States, India and Singapore. Frequent co-authors include Swagatam Das, Panayiotis Georgiou, Soumyadip Sengupta, Ponnuthurai Nagaratnam Suganthan, Udit Halder, Dipankar Maity, Shubhashis Sengupta, Athanasios V. Vasilakos, Witold Pedrycz and Shrikanth Narayanan. Their work appears in journals such as PLoS ONE, Information Sciences, Soft Computing, JMIR Public Health and Surveillance and Animal Behaviour.
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.