Munish Bhatia

1.9k total citations
104 papers, 1.2k citations indexed

About

Munish Bhatia is a scholar working on Computer Networks and Communications, Information Systems and Industrial and Manufacturing Engineering. According to data from OpenAlex, Munish Bhatia has authored 104 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Computer Networks and Communications, 22 papers in Information Systems and 19 papers in Industrial and Manufacturing Engineering. Recurrent topics in Munish Bhatia's work include IoT and Edge/Fog Computing (36 papers), Digital Transformation in Industry (19 papers) and Context-Aware Activity Recognition Systems (10 papers). Munish Bhatia is often cited by papers focused on IoT and Edge/Fog Computing (36 papers), Digital Transformation in Industry (19 papers) and Context-Aware Activity Recognition Systems (10 papers). Munish Bhatia collaborates with scholars based in India, Saudi Arabia and Italy. Munish Bhatia's co-authors include Sandeep K. Sood, Ankush Manocha, Simranpreet Kaur, Tariq Ahamed Ahanger, Abdullah Alqahtani, Shtwai Alsubai, Giovanni Stea, Sapna Kumari, Gulshan Kumar and Amit Sharma and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Internet of Things Journal.

In The Last Decade

Munish Bhatia

91 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Munish Bhatia India 19 492 336 254 154 149 104 1.2k
Parvaneh Asghari Iran 15 691 1.4× 431 1.3× 232 0.9× 137 0.9× 57 0.4× 39 1.3k
BalaAnand Muthu China 20 264 0.5× 301 0.9× 334 1.3× 177 1.1× 58 0.4× 55 1.3k
Hissam Tawfik United Kingdom 20 517 1.1× 304 0.9× 340 1.3× 239 1.6× 95 0.6× 106 1.6k
Waleed S. Alnumay Saudi Arabia 22 729 1.5× 484 1.4× 407 1.6× 109 0.7× 115 0.8× 54 1.6k
Asif Irshad Khan Saudi Arabia 21 489 1.0× 417 1.2× 417 1.6× 96 0.6× 45 0.3× 89 1.6k
Mehdi Adda Canada 19 166 0.3× 212 0.6× 322 1.3× 203 1.3× 98 0.7× 108 1.2k
Valery V. Korotaev Russia 17 658 1.3× 298 0.9× 178 0.7× 189 1.2× 65 0.4× 86 1.4k
Abdur Rahim Mohammad Forkan Australia 16 272 0.6× 127 0.4× 215 0.8× 284 1.8× 107 0.7× 51 1.1k
Sabah Mohammed Canada 16 265 0.5× 200 0.6× 376 1.5× 124 0.8× 49 0.3× 157 1.2k
Deepali Gupta India 22 341 0.7× 334 1.0× 364 1.4× 248 1.6× 35 0.2× 188 1.6k

Countries citing papers authored by Munish Bhatia

Since Specialization
Citations

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

Fields of papers citing papers by Munish Bhatia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Munish Bhatia

This figure shows the co-authorship network connecting the top 25 collaborators of Munish Bhatia. A scholar is included among the top collaborators of Munish Bhatia 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 Munish Bhatia. Munish Bhatia 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.
Bhatia, Munish, et al.. (2025). Bibliometric Study of Digital Twin for Sustainable Cities and Society. 3(4). 1–33.
2.
Alsubai, Shtwai, Mogeeb A. A. Mosleh, Suheer Al-Hadhrami, & Munish Bhatia. (2025). Artificial intelligence-inspired comprehensive framework for desertification prediction. 6. 462–476. 1 indexed citations
3.
Bhatia, Munish, et al.. (2025). The role of digital twin in urban infrastructure and building management: a global scientometric perspective. Cluster Computing. 29(1). 1 indexed citations
4.
Bhatia, Munish, et al.. (2025). Digital Twin and sustainability: A data-driven scientometric exploration. Internet of Things. 32. 101652–101652.
5.
Manocha, Ankush, Sandeep K. Sood, & Munish Bhatia. (2024). Federated learning-inspired smart ECG classification: an explainable artificial intelligence approach. Multimedia Tools and Applications. 84(19). 21673–21696. 2 indexed citations
6.
Ahanger, Tariq Ahamed, et al.. (2024). Quantum Informative Analysis in Smart Power Distribution. ACM Transactions on Intelligent Systems and Technology. 15(6). 1–18. 2 indexed citations
7.
Sood, Sandeep K., et al.. (2024). Extraction of emerging trends in quantum algorithm archives. Neural Computing and Applications. 36(29). 17851–17880. 5 indexed citations
8.
Alqahtani, Abdullah, et al.. (2024). Blockchain-inspired intelligent framework for logistic theft control. Journal of Network and Computer Applications. 234. 104055–104055. 3 indexed citations
9.
Alqahtani, Abdullah, et al.. (2024). IoT-Inspired Smart Theft Control Framework for Logistic Industry. IEEE Internet of Things Journal. 11(23). 38327–38336. 2 indexed citations
10.
Alsubai, Shtwai, et al.. (2024). Decision-Tree-Assisted Intelligent Framework for Food Quality Analysis. IEEE Internet of Things Journal. 11(19). 30800–30807. 3 indexed citations
11.
Manocha, Ankush, et al.. (2024). Enhancing sensor data reliability in structural health monitoring systems using digital twin technology. Structural Concrete. 26(5). 5919–5935. 1 indexed citations
12.
Alqahtani, Abdullah, Shtwai Alsubai, & Munish Bhatia. (2024). Applied artificial intelligence framework for smart evacuation in industrial disasters. Applied Intelligence. 54(11-12). 7030–7045. 4 indexed citations
13.
Bhatia, Munish, Tariq Ahamed Ahanger, & Ankush Manocha. (2023). Artificial intelligence based real-time earthquake prediction. Engineering Applications of Artificial Intelligence. 120. 105856–105856. 32 indexed citations
14.
Ahanger, Tariq Ahamed, et al.. (2023). IoT-Inspired Smart Disaster Evacuation Framework. IEEE Internet of Things Journal. 11(7). 12885–12892. 4 indexed citations
15.
Alqahtani, Abdullah, Shtwai Alsubai, Mohemmed Sha, & Munish Bhatia. (2023). Game Theoretic Systematic Approach for Transportation Quality Assessment. Mobile Networks and Applications. 29(4). 1165–1180. 2 indexed citations
16.
Kumari, Sapna & Munish Bhatia. (2022). A cognitive framework based on deep neural network for classification of coronavirus disease. Journal of Ambient Intelligence and Humanized Computing. 14(9). 12075–12089. 2 indexed citations
17.
Manocha, Ankush, Gulshan Kumar, Munish Bhatia, & Amit Sharma. (2020). Video-assisted smart health monitoring for affliction determination based on fog analytics. Journal of Biomedical Informatics. 109. 103513–103513. 10 indexed citations
18.
Bhatia, Munish, et al.. (2020). Internet of things-inspired healthcare system for urine-based diabetes prediction. Artificial Intelligence in Medicine. 107. 101913–101913. 49 indexed citations
19.
Manocha, Ankush, Ramandeep Singh, & Munish Bhatia. (2019). Cognitive Intelligence Assisted Fog-Cloud Architecture for Generalized Anxiety Disorder (GAD) Prediction. Journal of Medical Systems. 44(1). 7–7. 16 indexed citations
20.
Bhatia, Munish & Sandeep K. Sood. (2016). Temporal Informative Analysis in Smart-ICU Monitoring: M-HealthCare Perspective. Journal of Medical Systems. 40(8). 190–190. 60 indexed citations

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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