Yugal Kumar
Impact in
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- Artificial Intelligence in Healthcare
- Artificial Intelligence top 2%
- Metaheuristic Optimization Algorithms Research
- Advanced Clustering Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
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- Metaheuristic Optimization Algorithms Research 26
- Advanced Clustering Algorithms Research 16
- Data Stream Mining Techniques 8
- Evolutionary Algorithms and Applications 7
- Imbalanced Data Classification Techniques 7
- Co-authors
- G. Sahoo (15 shared papers)Pradeep Kumar Singh (12 shared papers)Pardeep Kumar (7 shared papers)Amit Sharma (1 shared paper)Raghavendra Kumar (5 shared papers)Divyansh Thakur (4 shared papers)Arvinder Kaur (10 shared papers)Girija Shankar Sahoo (2 shared papers)
In The Last Decade
Yugal Kumar
77 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 143
- Health Information Management 160
- Artificial Intelligence 565
- Health Informatics 14
- Safety, Risk, Reliability and Quality 91
- Computer Networks and Communications 205
Countries citing papers authored by Yugal Kumar
This map shows the geographic impact of Yugal Kumar'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 Yugal Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yugal Kumar more than expected).
Fields of papers citing papers by Yugal Kumar
This network shows the impact of papers produced by Yugal Kumar. 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 Yugal Kumar. The network helps show where Yugal Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Yugal Kumar, 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 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 169 | |
| 2 | 2019 | 127 | |
| 3 | 2017 | 67 | |
| 4 | 2020 | 62 | |
| 5 | 2015 | 62 | |
| 6 | 2017 | 55 | |
| 7 | 2018 | 54 | |
| 8 | 2014 | 50 | |
| 9 | 2020 | 47 | |
| 10 | 2016 | 45 | |
| 11 | 2013 | 44 | |
| 12 | 2021 | 41 | |
| 13 | 2012 | 40 | |
| 14 | 2014 | 40 | |
| 15 | 2020 | 37 | |
| 16 | 2021 | 34 | |
| 17 | 2015 | 28 | |
| 18 | 2012 | 28 | |
| 19 | 2015 | 27 | |
| 20 | 2014 | 26 |
About Yugal Kumar
Yugal Kumar is a scholar working on Artificial Intelligence, Computer Networks and Communications, Health Information Management, Information Systems and Computer Vision and Pattern Recognition, having authored 87 papers that have together received 1.5k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (26 papers), Advanced Clustering Algorithms Research (16 papers), Artificial Intelligence in Healthcare (12 papers), Data Stream Mining Techniques (8 papers), Evolutionary Algorithms and Applications (7 papers), Imbalanced Data Classification Techniques (7 papers), Stock Market Forecasting Methods (6 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Health Information Management (160 citations), Artificial Intelligence (565 citations), Health Informatics (14 citations), Safety, Risk, Reliability and Quality (91 citations) and Computer Networks and Communications (205 citations). Yugal Kumar has collaborated with scholars based in India, Malaysia and Russia. Frequent co-authors include G. Sahoo, Pradeep Kumar Singh, Pardeep Kumar, Amit Sharma, Raghavendra Kumar, Divyansh Thakur, Arvinder Kaur, Girija Shankar Sahoo, Vijendra Singh and Anand Srivastava. Their work appears in journals such as Evolutionary Intelligence, Applied Intelligence, Neural Computing and Applications, International Journal of Embedded Systems and Big Data.
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.