Anupam Kumar Bairagi

3.3k total citations · 4 hit papers
70 papers, 2.0k citations indexed

About

Anupam Kumar Bairagi is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Anupam Kumar Bairagi has authored 70 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Networks and Communications, 19 papers in Electrical and Electronic Engineering and 17 papers in Artificial Intelligence. Recurrent topics in Anupam Kumar Bairagi's work include IoT and Edge/Fog Computing (12 papers), Advanced MIMO Systems Optimization (10 papers) and Blockchain Technology Applications and Security (8 papers). Anupam Kumar Bairagi is often cited by papers focused on IoT and Edge/Fog Computing (12 papers), Advanced MIMO Systems Optimization (10 papers) and Blockchain Technology Applications and Security (8 papers). Anupam Kumar Bairagi collaborates with scholars based in Bangladesh, South Korea and Saudi Arabia. Anupam Kumar Bairagi's co-authors include Mehedi Masud, Choong Seon Hong, Nguyen H. Tran, Niloy Sikder, Abdullah-Al Nahid, Madyan Alsenwi, Mehdi Bennis, Mohammed A. AlZain, Shashi Raj Pandey and Saydul Akbar Murad and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Anupam Kumar Bairagi

66 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework

2021 295 citations Mehedi Masud, Anupam Kumar Bairagi et al. Sensors profile →
Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach

2021 223 citations Madyan Alsenwi, Nguyen H. Tran et al. University of Oulu Repository (University of Oulu) profile →
IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review

2022 148 citations Anupam Kumar Bairagi et al. profile →
Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning

2022 118 citations Nusrat Jahan Prottasha, Md. Kowsher et al. Sensors profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anupam Kumar Bairagi Bangladesh	25	600	594	539	427	240	70	2.0k
Kalpna Guleria India	20	492 0.8×	243 0.4×	426 0.8×	318 0.7×	170 0.7×	156	1.9k
Abeer D. Algarni Saudi Arabia	23	428 0.7×	401 0.7×	629 1.2×	216 0.5×	523 2.2×	153	2.2k
Naveed Islam Pakistan	21	785 1.3×	300 0.5×	700 1.3×	402 0.9×	467 1.9×	58	2.0k
Mohammad Shorfuzzaman Saudi Arabia	28	351 0.6×	177 0.3×	714 1.3×	443 1.0×	510 2.1×	108	2.3k
Ramesh Chandra Poonia India	22	312 0.5×	266 0.4×	449 0.8×	216 0.5×	255 1.1×	129	1.7k
Mangal Sain South Korea	18	556 0.9×	193 0.3×	503 0.9×	384 0.9×	205 0.9×	107	1.6k
Farhan Aadil Pakistan	24	817 1.4×	720 1.2×	391 0.7×	120 0.3×	242 1.0×	62	1.9k
Sami Bourouis Saudi Arabia	29	424 0.7×	206 0.3×	845 1.6×	249 0.6×	596 2.5×	110	2.5k
Asif Karim Australia	24	286 0.5×	222 0.4×	910 1.7×	536 1.3×	282 1.2×	81	2.1k
Sultan S. Alshamrani Saudi Arabia	22	344 0.6×	294 0.5×	458 0.8×	154 0.4×	353 1.5×	113	1.7k

Countries citing papers authored by Anupam Kumar Bairagi

Since Specialization

Citations

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

Fields of papers citing papers by Anupam Kumar Bairagi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anupam Kumar Bairagi. 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 Anupam Kumar Bairagi. The network helps show where Anupam Kumar Bairagi may publish in the future.

Co-authorship network of co-authors of Anupam Kumar Bairagi

This figure shows the co-authorship network connecting the top 25 collaborators of Anupam Kumar Bairagi. A scholar is included among the top collaborators of Anupam Kumar Bairagi 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 Anupam Kumar Bairagi. Anupam Kumar Bairagi 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:

20 of 20 papers shown

Miah, Abu Saleh Musa, M. Raihan, Mohammad Javad Kabir, et al.. (2025). DiaBD: A novel benchmark dataset for diabetes prediction. Alexandria Engineering Journal. 132. 435–455. 1 indexed citations

Hassan, Md. Mehedi, et al.. (2024). Synergy of 6G technology and IoT networks for transformative applications. International Journal of Communication Systems. 37(14). 4 indexed citations

Hassan, Md. Mehedi, Md. Mahedi Hassan, Farhana Yasmin, et al.. (2023). Machine Learning-Based Rainfall Prediction: Unveiling Insights and Forecasting for Improved Preparedness. IEEE Access. 11. 132196–132222. 27 indexed citations

Hassan, Md. Mehedi, Md. Mehedi Hassan, Md. Mahedi Hassan, et al.. (2023). A comparative assessment of machine learning algorithms with the Least Absolute Shrinkage and Selection Operator for breast cancer detection and prediction. Decision Analytics Journal. 7. 100245–100245. 42 indexed citations

Biswas, Sujit, et al.. (2023). Interoperability Benefits and Challenges in Smart City Services: Blockchain as a Solution. Electronics. 12(4). 1036–1036. 11 indexed citations

Rahman, Md Arifur, et al.. (2023). An Improved Encoder-Decoder CNN with Region-Based Filtering for Vibrant Colorization. Computer Systems Science and Engineering. 46(1). 1059–1077. 6 indexed citations

Adhikary, Apurba, Avi Deb Raha, Mohammad Amzad Hossain, et al.. (2023). An Explainable Artificial Intelligence Framework for the Predictive Analysis of Hypo and Hyper Thyroidism Using Machine Learning Algorithms. SHILAP Revista de lepidopterología. 3(3). 211–231. 19 indexed citations

Hassan, Md. Mehedi, et al.. (2023). A Comparative Study, Prediction and Development of Chronic Kidney Disease Using Machine Learning on Patients Clinical Records. SHILAP Revista de lepidopterología. 3(2). 92–104. 27 indexed citations

Yasmin, Farhana, Md. Mehedi Hassan, Sadika Zaman, et al.. (2023). GastroNet: Gastrointestinal Polyp and Abnormal Feature Detection and Classification With Deep Learning Approach. IEEE Access. 11. 97605–97624. 8 indexed citations

10.

Raihan, M., et al.. (2023). A Smartphone-Based Detection System for Tomato Leaf Disease Using EfficientNetV2B2 and Its Explainability with Artificial Intelligence (AI). Sensors. 23(21). 8685–8685. 10 indexed citations

11.

Murad, Saydul Akbar, et al.. (2023). Priority Based Fair Scheduling: Enhancing Efficiency in Cloud Job Distribution. 1. 170–175. 1 indexed citations

12.

Prottasha, Nusrat Jahan, Saydul Akbar Murad, Abu Jafar Md Muzahid, et al.. (2023). Impact learning: A learning method from feature’s impact and competition. Journal of Computational Science. 69. 102011–102011. 3 indexed citations

13.

Adhikary, Apurba, et al.. (2022). Performance evaluation of micro lens arrays: Improvement of light intensity and efficiency of white organic light emitting diodes. PLoS ONE. 17(5). e0269134–e0269134. 2 indexed citations

14.

Alsenwi, Madyan, Nguyen H. Tran, Mehdi Bennis, et al.. (2021). Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach. University of Oulu Repository (University of Oulu). 223 indexed citations breakdown →

15.

Raihan, M., et al.. (2021). A Machine Learning Based Study to Predict Depression with Monitoring Actigraph Watch Data. 1–5. 10 indexed citations

16.

Bairagi, Anupam Kumar, Nguyen H. Tran, & Choong Seon Hong. (2018). A multi-game approach for effective co-existence in unlicensed spectrum between LTE-U system and Wi-Fi access point. 380–385. 12 indexed citations

17.

Bairagi, Anupam Kumar, et al.. (2018). Reverse Path Activation-based Reverse Influence Maximization in Social Networks. Journal of KIISE. 45(11). 1203–1209. 5 indexed citations

18.

Abedin, Sarder Fakhrul, et al.. (2016). Process Migration Using Docker Container in SDN Environment. 한국정보과학회 학술발표논문집. 1331–1333. 1 indexed citations

19.

Alam, Md. Golam Rabiul, et al.. (2016). Deep Learning based Emotion Recognition through Biosensor Observations. 한국정보과학회 학술발표논문집. 1231–1232. 3 indexed citations

20.

Alam, Md. Golam Rabiul, Nguyen H. Tran, T. Cuong, et al.. (2014). Distributed Reinforcement Learning based Code Offloading in Mobile Fog. 한국정보과학회 학술발표논문집. 285–287. 1 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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