Ajit Kumar Nayak
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Co-authors
- Amrutanshu PanigrahiRaghvendra MallSrikanta PatnaikBibhuprasad SahuHimansu DasSatchidananda DehuriBijaya Ketan PanigrahiBhabani Shankar Prasad Mishra
- Topics
- Speech Recognition and Synthesis (18 papers)Natural Language Processing Techniques (15 papers)Mobile Ad Hoc Networks (12 papers)
In The Last Decade
Ajit Kumar Nayak
62 papers receiving 337 citations
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 136
- Computer Networks and Communications 134
- Signal Processing 73
- Electrical and Electronic Engineering 73
- Information Systems 48
Countries citing papers authored by Ajit Kumar Nayak
This map shows the geographic impact of Ajit Kumar Nayak'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 Ajit Kumar Nayak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ajit Kumar Nayak more than expected).
Fields of papers citing papers by Ajit Kumar Nayak
This network shows the impact of papers produced by Ajit Kumar Nayak. 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 Ajit Kumar Nayak. The network helps show where Ajit Kumar Nayak may publish in the future.
Co-authorship network of co-authors of Ajit Kumar Nayak
This figure shows the co-authorship network connecting the top 25 collaborators of Ajit Kumar Nayak. A scholar is included among the top collaborators of Ajit Kumar Nayak 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 Ajit Kumar Nayak. Ajit Kumar Nayak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 15 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | A Semi-supervised Learning of HMM to Build a POS Tagger for a Low Resourced Language | 5 |
| 12 | 1 | |
| 13 | 3 | |
| 14 | 3 | |
| 15 | 4 | |
| 16 | 11 | |
| 17 | Odia Characters Recognition by Training Tesseract OCR Engine | 5 |
| 18 | Mixed Convective MHD Flow of Second Grade Fluid with Viscous Dissipation and Joule Heating Past a Vertical Infinite Plate with Mass Transfer | 2 |
| 19 | 8 | |
| 20 | EVALUATIN OF QoS PARAMETERS ON TCP/IP IN WIRELESS AD HOC NETWORKS | 3 |
About Ajit Kumar Nayak
Ajit Kumar Nayak is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications, having authored 67 papers that have together received 369 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (18 papers), Natural Language Processing Techniques (15 papers) and Mobile Ad Hoc Networks (12 papers). The work is most often cited by research in Signal Processing (73 citations), Computer Networks and Communications (134 citations) and Artificial Intelligence (136 citations). Ajit Kumar Nayak has collaborated with scholars based in India, Singapore and Australia. Frequent co-authors include Amrutanshu Panigrahi, Raghvendra Mall, Srikanta Patnaik, Bibhuprasad Sahu, Himansu Das, Satchidananda Dehuri, Bijaya Ketan Panigrahi, Bhabani Shankar Prasad Mishra, Alok Kumar Jagadev and Binod Kumar Pattanayak. Their work appears in journals such as IEEE Access, Computer Communications and Multimedia Systems.
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.