Rohit Bajaj

678 total citations
48 papers, 320 citations indexed

About

Rohit Bajaj is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Rohit Bajaj has authored 48 papers receiving a total of 320 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Networks and Communications, 13 papers in Electrical and Electronic Engineering and 8 papers in Artificial Intelligence. Recurrent topics in Rohit Bajaj's work include Mobile Ad Hoc Networks (5 papers), IoT and Edge/Fog Computing (4 papers) and Wireless Body Area Networks (4 papers). Rohit Bajaj is often cited by papers focused on Mobile Ad Hoc Networks (5 papers), IoT and Edge/Fog Computing (4 papers) and Wireless Body Area Networks (4 papers). Rohit Bajaj collaborates with scholars based in India, Malaysia and Jordan. Rohit Bajaj's co-authors include Mamta Sharma, D. Bahadur, Jaspreet Singh, Deepika Sharma, Gagangeet Singh Aujla, Sanjay Sood, Yogesh Kumar, Navneet Kaur, Rohit Kumar and Shruti Agarwal and has published in prestigious journals such as Scientific Reports, Dalton Transactions and Soft Computing.

In The Last Decade

Rohit Bajaj

32 papers receiving 314 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rohit Bajaj India 10 89 79 51 51 50 48 320
P. Suresh India 10 36 0.4× 87 1.1× 61 1.2× 50 1.0× 47 0.9× 49 344
R Saravanakumar India 12 180 2.0× 48 0.6× 87 1.7× 61 1.2× 102 2.0× 62 451
Haoxin Wang China 10 114 1.3× 70 0.9× 51 1.0× 75 1.5× 33 0.7× 34 313
Akhilesh Singh India 16 294 3.3× 83 1.1× 80 1.6× 50 1.0× 19 0.4× 49 639
K. Mahalakshmi India 10 126 1.4× 42 0.5× 41 0.8× 116 2.3× 48 1.0× 55 351
Yinhao Li China 9 40 0.4× 79 1.0× 76 1.5× 38 0.7× 25 0.5× 40 305
K. Raja India 11 62 0.7× 32 0.4× 145 2.8× 30 0.6× 68 1.4× 65 451
S. Gopal Krishna Patro India 11 28 0.3× 38 0.5× 70 1.4× 31 0.6× 11 0.2× 38 322
Atul Kumar India 10 53 0.6× 128 1.6× 62 1.2× 50 1.0× 7 0.1× 49 343

Countries citing papers authored by Rohit Bajaj

Since Specialization
Citations

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

Fields of papers citing papers by Rohit Bajaj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rohit Bajaj

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

All Works

20 of 20 papers shown
1.
Bajaj, Rohit, et al.. (2025). A robust and statistical analyzed predictive model for drug toxicity using machine learning. Scientific Reports. 15(1). 17993–17993.
2.
Bajaj, Rohit, et al.. (2025). An Optimised Model for Arrhythmia Prediction using FSM. 1–7.
3.
Bajaj, Rohit, et al.. (2025). Optimized Ensemble Model to Predict the Compatibility of Automobiles With Hybrid Electric Vehicles. Journal of Electrical and Computer Engineering. 2025(1).
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Meenakshi, Meenakshi, et al.. (2023). Descriptive Analysis of Feature Selection and Clustering Algorithms for Optimized Drug Toxicity Prediction Model. 6. 2182–2186. 1 indexed citations
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Kaur, Navneet, et al.. (2022). Energy Efficient MAC Framework Under Temporal Fading in WBAN. 1–6.
10.
Kaur, Sumandeep, et al.. (2022). Abalone Age Prediction using Optimized Ensembel Model. 8. 1023–1027.
11.
Singh, Jaspreet, et al.. (2022). Prominent Features based Chronic Kidney Disease Prediction Model using Machine Learning. 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC). 1193–1198. 13 indexed citations
12.
Bajaj, Rohit, et al.. (2022). A Robust Machine Learning Model for Prediction: The Electroencephalography. 1270–1274. 23 indexed citations
13.
Bajaj, Rohit, et al.. (2022). An Optimized Ensemble Model for Early Breast Cancer Prediction. 1275–1279. 3 indexed citations
14.
Bajaj, Rohit, et al.. (2021). Performance Analysis of WSN by varying number of clusters. 4. 175–179. 2 indexed citations
15.
Sharma, Neha, et al.. (2019). Genetic Load Balancing Algorithms in Cloud Environment. International Journal of Innovative Technology and Exploring Engineering. 8(9S4). 98–103. 3 indexed citations
16.
Bajaj, Rohit, et al.. (2019). Effect On Lifetime Of Routing Protocols By Means Of Different Connectivity Schemes. International journal of scientific and technology research. 8(12). 617–622. 4 indexed citations
17.
Kumar, Rohit, et al.. (2018). Energy Efficient Communication Using Reconfigurable Directional Antenna in MANET. Procedia Computer Science. 125. 194–200. 15 indexed citations
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Bajaj, Rohit, Mamta Sharma, & D. Bahadur. (2013). Visible light-driven novel nanocomposite (BiVO4/CuCr2O4) for efficient degradation of organic dye. Dalton Transactions. 42(19). 6736–6736. 73 indexed citations
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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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