Bighnaraj Naik
- Artificial Intelligence top 1%
- Computer Networks and Communications top 5%
- Electrical and Electronic Engineering top 10%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Janmenjoy NayakH. S. BeheraDanilo PelusiManohar MishraH. SwapnarekhaPandit Byomakesha DashHimansu DasAjith Abraham
- Topics
- Metaheuristic Optimization Algorithms Research (21 papers)Neural Networks and Applications (13 papers)Machine Learning and ELM (10 papers)
- Partner nations
- IndiaItalyUnited States
In The Last Decade
Bighnaraj Naik
90 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Artificial Intelligence 1.2k
- Computer Networks and Communications 419
- Electrical and Electronic Engineering 418
- Information Systems 358
- Computer Vision and Pattern Recognition 313
Countries citing papers authored by Bighnaraj Naik
This map shows the geographic impact of Bighnaraj Naik'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 Bighnaraj Naik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bighnaraj Naik more than expected).
Fields of papers citing papers by Bighnaraj Naik
This network shows the impact of papers produced by Bighnaraj Naik. 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 Bighnaraj Naik. The network helps show where Bighnaraj Naik may publish in the future.
Co-authorship network of co-authors of Bighnaraj Naik
This figure shows the co-authorship network connecting the top 25 collaborators of Bighnaraj Naik. A scholar is included among the top collaborators of Bighnaraj Naik based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bighnaraj Naik. Bighnaraj Naik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 25 Years of Particle Swarm Optimization: Flourishing Voyage of Two Decadesbreakdown → | 133 |
| 5 | 1 | |
| 6 | 55 | |
| 7 | 2 | |
| 8 | 10 | |
| 9 | 42 | |
| 10 | 39 | |
| 11 | 3 | |
| 12 | 18 | |
| 13 | 1 | |
| 14 | 2 | |
| 15 | 131 | |
| 16 | 46 | |
| 17 | 24 | |
| 18 | 52 | |
| 19 | 17 | |
| 20 | 210 |
About Bighnaraj Naik
Bighnaraj Naik is a scholar working on Artificial Intelligence, Health Informatics and Software, having authored 94 papers that have together received 2.7k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (21 papers), Neural Networks and Applications (13 papers) and Machine Learning and ELM (10 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Software (126 citations) and Health Informatics (35 citations). Bighnaraj Naik has collaborated with scholars based in India, Italy and United States. Frequent co-authors include Janmenjoy Nayak, H. S. Behera, Danilo Pelusi, Manohar Mishra, H. Swapnarekha, Pandit Byomakesha Dash, Himansu Das, Ajith Abraham, Luca G. Tallini and Raffaele Mascella. Their work appears in journals such as Expert Systems with Applications, Sensors and IEEE Transactions on Industrial Informatics.
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.