Yugal Kumar

2.4k citations
100 papers · 1.8k · h-index 25

Impact in

Papers in

Yugal Kumar

91 papers receiving 1.7k citations

Peers

Yugal Kumar
Comparison fields: 5 of 144
  • Health Information Management 195
  • Artificial Intelligence 689
  • Health Informatics 19
  • Safety, Risk, Reliability and Quality 101
  • Computer Networks and Communications 260
Replace Noorbakhsh Amiri Golilarz with:
Noorbakhsh Amiri Golilarz China
Atta Rahman Saudi Arabia
Bernard Kamsu-Foguem France
Tania Cerquitelli Italy
Gang Luo United States
Sudan Jha India
Rohit Sharma India
Stefania Montani Italy
Michael G. Madden Ireland
Georgios Douzas Portugal
Yugal Kumar relative to Noorbakhsh Amiri Golilarz China Noorbakhsh Amiri Golilarz's profile →
Citations per field
00.5×20×40×65×
Noorbakhsh Amiri Golilarz · 1×
Citations per year

Countries citing papers authored by Yugal Kumar

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Yugal Kumar Line = papers co-authored together Yugal Kumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 100 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020182
2 2019147
3 201778
4 202074
5 201571
6 201758
7 201857
8 201657
9 201456
10 202051
11 201350
12 201447
13 201244
14 202144
15 202041
16 202139
17 201839
18 201236
19 201431
20 201529

About Yugal Kumar

Yugal Kumar is a scholar working on Artificial Intelligence, Computer Networks and Communications, Health Information Management, Computer Vision and Pattern Recognition and Information Systems, having authored 100 papers that have together received 1.8k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (30 papers), Advanced Clustering Algorithms Research (19 papers), Artificial Intelligence in Healthcare (15 papers), Data Stream Mining Techniques (8 papers), Face and Expression Recognition (7 papers), Stock Market Forecasting Methods (7 papers), Evolutionary Algorithms and Applications (7 papers) and Imbalanced Data Classification Techniques (7 papers). The work is most often cited by research in Health Information Management (195 citations), Artificial Intelligence (689 citations), Health Informatics (19 citations), Safety, Risk, Reliability and Quality (101 citations) and Computer Networks and Communications (260 citations). Yugal Kumar has collaborated with scholars based in India, Russia and Malaysia. 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 Geeta Yadav. Their work appears in journals such as Applied Intelligence, Evolutionary 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.

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