Rajnish Ratna

519 total citations
10 papers, 317 citations indexed

About

Rajnish Ratna is a scholar working on Information Systems, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Rajnish Ratna has authored 10 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Information Systems, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Rajnish Ratna's work include Emotion and Mood Recognition (2 papers), Speech and Audio Processing (2 papers) and IoT and Edge/Fog Computing (1 paper). Rajnish Ratna is often cited by papers focused on Emotion and Mood Recognition (2 papers), Speech and Audio Processing (2 papers) and IoT and Edge/Fog Computing (1 paper). Rajnish Ratna collaborates with scholars based in Bhutan, India and Saudi Arabia. Rajnish Ratna's co-authors include Mohammed Zakariah, Wesam Atef Hatamleh, Abeer Ali Alnuaim, Hussam Tarazi, Prashant Kumar Shukla, Aseel Alhadlaq, Tariq Ahamed Ahanger, Anil Audumbar Pise, Nidhi Arora and Hashem O. Alsaab and has published in prestigious journals such as Computational Intelligence and Neuroscience, Wireless Communications and Mobile Computing and Journal of Food Quality.

In The Last Decade

Rajnish Ratna

9 papers receiving 268 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Rajnish Ratna Bhutan	6	99	54	47	39	35	10	317
Shazia Afzal United Kingdom	9	155 1.6×	69 1.3×	18 0.4×	11 0.3×	49 1.4×	15	355
Imrus Salehin Bangladesh	10	92 0.9×	16 0.3×	17 0.4×	17 0.4×	46 1.3×	24	359
Theodor Panagiotakopoulos Greece	12	63 0.6×	21 0.4×	17 0.4×	9 0.2×	29 0.8×	52	376
Ekkarat Boonchieng Thailand	10	65 0.7×	63 1.2×	17 0.4×	41 1.1×	34 1.0×	55	389
Alper Özpınar Türkiye	8	76 0.8×	43 0.8×	71 1.5×	9 0.2×	206 5.9×	22	423
Li Cui China	10	100 1.0×	22 0.4×	10 0.2×	17 0.4×	103 2.9×	38	369
Lucia Cascone Italy	10	88 0.9×	16 0.3×	49 1.0×	4 0.1×	93 2.7×	35	293
Caslon Chua Australia	9	67 0.7×	59 1.1×	73 1.6×	4 0.1×	56 1.6×	47	318
Jyoti Agarwal India	8	80 0.8×	12 0.2×	16 0.3×	8 0.2×	21 0.6×	35	252
Daniel Braun Germany	10	209 2.1×	15 0.3×	6 0.1×	10 0.3×	46 1.3×	53	426

Countries citing papers authored by Rajnish Ratna

Since Specialization

Citations

This map shows the geographic impact of Rajnish Ratna'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 Rajnish Ratna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajnish Ratna more than expected).

Fields of papers citing papers by Rajnish Ratna

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rajnish Ratna. 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 Rajnish Ratna. The network helps show where Rajnish Ratna may publish in the future.

Co-authorship network of co-authors of Rajnish Ratna

This figure shows the co-authorship network connecting the top 25 collaborators of Rajnish Ratna. A scholar is included among the top collaborators of Rajnish Ratna 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 Rajnish Ratna. Rajnish Ratna is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Arora, Nidhi, et al.. (2022). Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education. Computational Intelligence and Neuroscience. 2022. 1–8. 56 indexed citations

2.

Gupta, Kamali, et al.. (2022). An Energy‐Efficient Partial Data Offloading‐Based Priority Rate Controller Technique in Edge‐Based IoT Network to Improve QoS. Wireless Communications and Mobile Computing. 2022(1). 2 indexed citations

3.

Alnuaim, Abeer Ali, Mohammed Zakariah, Wesam Atef Hatamleh, et al.. (2022). Speaker Gender Recognition Based on Deep Neural Networks and ResNet50. Wireless Communications and Mobile Computing. 2022(1). 60 indexed citations

4.

Ratna, Rajnish, et al.. (2022). Impact of Teacher’s Leadership Style on Student’s Academic Performance: a case of Business school. 11(1). 71–91. 1 indexed citations

5.

Alnuaim, Abeer Ali, Mohammed Zakariah, Aseel Alhadlaq, et al.. (2022). Human-Computer Interaction with Detection of Speaker Emotions Using Convolution Neural Networks. Computational Intelligence and Neuroscience. 2022. 1–16. 47 indexed citations

6.

Gangadharan, Syam Machinathu Parambil, et al.. (2022). Detection of Adulteration in Food Using Recurrent Neural Network with Internet of Things. Journal of Food Quality. 2022. 1–11. 13 indexed citations

7.

Ahanger, Tariq Ahamed, et al.. (2022). A Machine Learning-Based Water Potability Prediction Model by Using Synthetic Minority Oversampling Technique and Explainable AI. Computational Intelligence and Neuroscience. 2022. 1–15. 44 indexed citations

8.

Alnuaim, Abeer Ali, Mohammed Zakariah, Prashant Kumar Shukla, et al.. (2022). Human-Computer Interaction for Recognizing Speech Emotions Using Multilayer Perceptron Classifier. Journal of Healthcare Engineering. 2022. 1–12. 92 indexed citations

9.

Ratna, Rajnish, et al.. (2019). EDUCATION IN BHUTAN: AN OBSERVATION FROM SUSTAINABILITY PERSPECTIVE. 6(3). 55–59. 2 indexed citations

10.

Ratna, Rajnish & Tanpreet Kaur. (2014). Measuring Impact of Trade Unions on Workmen Satisfaction in a Manufacturing unit.

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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