S. M. Riazul Islam

9.9k total citations · 4 hit papers
112 papers, 6.3k citations indexed

About

S. M. Riazul Islam is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Biomedical Engineering. According to data from OpenAlex, S. M. Riazul Islam has authored 112 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Electrical and Electronic Engineering, 43 papers in Computer Networks and Communications and 23 papers in Biomedical Engineering. Recurrent topics in S. M. Riazul Islam's work include IoT and Edge/Fog Computing (19 papers), Advanced Wireless Communication Technologies (16 papers) and Wireless Body Area Networks (13 papers). S. M. Riazul Islam is often cited by papers focused on IoT and Edge/Fog Computing (19 papers), Advanced Wireless Communication Technologies (16 papers) and Wireless Body Area Networks (13 papers). S. M. Riazul Islam collaborates with scholars based in South Korea, Bangladesh and United States. S. M. Riazul Islam's co-authors include Kyung Sup Kwak, Daehan Kwak, Mahmud Hossain, Md. Humaun Kabir, Shaker El–Sappagh, Farman Ali, Muhammad Imran, Amjad Ali, Octavia A. Dobre and Ming Zeng and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

S. M. Riazul Islam

110 papers receiving 5.9k 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.

The Internet of Things for Health Care: A Comprehensive Survey

2015 1.9k citations S. M. Riazul Islam, Md. Humaun Kabir et al. IEEE Access profile →
A smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion

2020 526 citations Farman Ali, Shaker El–Sappagh et al. profile →
An intelligent healthcare monitoring framework using wearable sensors and social networking data

2020 241 citations Farman Ali, Shaker El–Sappagh et al. profile →
A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer’s disease

2021 210 citations Shaker El–Sappagh, S. M. Riazul Islam et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. M. Riazul Islam South Korea	34	2.2k	1.7k	1.3k	1.2k	1.0k	112	6.3k
Sungyoung Lee South Korea	41	1.8k 0.8×	893 0.5×	2.1k 1.6×	473 0.4×	1.6k 1.5×	361	6.5k
Kyung Sup Kwak South Korea	45	5.4k 2.4×	4.0k 2.3×	1.9k 1.5×	2.8k 2.3×	1.7k 1.6×	606	11.4k
Mazin Abed Mohammed Iraq	49	2.0k 0.9×	651 0.4×	2.9k 2.3×	489 0.4×	1.3k 1.2×	258	8.3k
Yixue Hao China	30	3.1k 1.4×	1.5k 0.9×	1.0k 0.8×	426 0.3×	1.0k 1.0×	87	5.3k
Daehan Kwak United States	17	1.5k 0.7×	566 0.3×	779 0.6×	572 0.5×	867 0.8×	75	3.4k
Gunasekaran Manogaran United States	45	1.6k 0.7×	734 0.4×	1.7k 1.4×	463 0.4×	1.4k 1.3×	122	6.6k
Pubudu N. Pathirana Australia	34	2.3k 1.0×	1.8k 1.0×	1.6k 1.2×	566 0.5×	1.3k 1.3×	241	6.4k
Ketan Kotecha India	41	815 0.4×	1.1k 0.7×	2.0k 1.6×	466 0.4×	795 0.8×	397	7.6k
K. Shankar India	47	1.8k 0.8×	757 0.4×	2.1k 1.6×	349 0.3×	1.5k 1.4×	206	6.5k
Chinmay Chakraborty India	38	1.2k 0.5×	591 0.3×	1.4k 1.1×	329 0.3×	830 0.8×	195	4.5k

Countries citing papers authored by S. M. Riazul Islam

Since Specialization

Citations

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

Fields of papers citing papers by S. M. Riazul Islam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. M. Riazul Islam. 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 S. M. Riazul Islam. The network helps show where S. M. Riazul Islam may publish in the future.

Co-authorship network of co-authors of S. M. Riazul Islam

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

All Works

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20 of 20 papers shown

Nahiduzzaman, Md., Lway Faisal Abdulrazak, Mohamed Arselene Ayari, Amith Khandakar, & S. M. Riazul Islam. (2024). A novel framework for lung cancer classification using lightweight convolutional neural networks and ridge extreme learning machine model with SHapley Additive exPlanations (SHAP). Expert Systems with Applications. 248. 123392–123392. 30 indexed citations

Hossain, Mahmud, et al.. (2023). A Survey on Consensus Algorithms in Blockchain-Based Applications: Architecture, Taxonomy, and Operational Issues. IEEE Access. 11. 39066–39082. 24 indexed citations

Islam, S. M. Riazul, et al.. (2023). A SURVEY ON MOBILE CLOUD COMPUTING PROBLEMS AND SOLUTIONS. Pakistan Journal of Science. 75(1). 71–77.

Haider, Sajjad, et al.. (2022). A Deep Learning Model for Remaining Useful Life Prediction of Aircraft Turbofan Engine on C-MAPSS Dataset. IEEE Access. 10. 95425–95440. 46 indexed citations

Islam, S. M. Riazul, et al.. (2022). A novel hybrid meta-heuristic contrast stretching technique for improved skin lesion segmentation. Computers in Biology and Medicine. 151(Pt A). 106222–106222. 12 indexed citations

Badrudduza, A. S. M., et al.. (2021). On the Intercept Probability and Secure Outage Analysis of Mixed ( α – κ – μ )-Shadowed and Málaga Turbulent Models. IEEE Access. 9. 133849–133860. 10 indexed citations

Badrudduza, A. S. M., S. M. Riazul Islam, Milton Kumar Kundu, et al.. (2021). Secrecy Performance Analysis of Mixed α − μ and Exponentiated Weibull RF-FSO Cooperative Relaying System. IEEE Access. 9. 72342–72356. 28 indexed citations

Badrudduza, A. S. M., et al.. (2021). Impact of Correlation and Pointing Error on Secure Outage Performance Over Arbitrary Correlated Nakagami-$m$ and $\mathcal {M}$-Turbulent Fading Mixed RF-FSO Channel. IEEE photonics journal. 13(2). 1–17. 21 indexed citations

Islam, S. M. Riazul, et al.. (2021). Numerical Design and Investigation of Circularly Segmented Air Holes-Assisted Hollow-Core Terahertz Waveguide as Optical Chemical Sensor. IEEE Access. 9. 86155–86165. 9 indexed citations

10.

Nguyen, Minh‐Sang Van, Dinh‐Thuan Do, Fatemeh Afghah, S. M. Riazul Islam, & Anh‐Tu Le. (2021). Exploiting Secrecy Performance of Uplink NOMA in Cellular Networks. IEEE Access. 9. 95135–95154. 12 indexed citations

11.

Kader, Md. Fazlul, et al.. (2021). Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances. IEEE Access. 9. 37622–37655. 144 indexed citations

12.

Kabir, Md. Humaun, S. M. Riazul Islam, Anish Prasad Shrestha, et al.. (2021). Electromagnetic Nanocommunication Networks: Principles, Applications, and Challenges. IEEE Access. 9. 166147–166165. 13 indexed citations

13.

Akram, Tallha, S. M. Riazul Islam, Syed Rameez Naqvi, et al.. (2021). A novel framework for approximating resistance–temperature characteristics of a superconducting film based on artificial neural networks. Results in Physics. 24. 104088–104088. 2 indexed citations

14.

Badrudduza, A. S. M., S. M. Riazul Islam, Imran Shafique Ansari, et al.. (2020). On Secrecy Performance of Mixed Generalized Gamma and Málaga RF-FSO Variable Gain Relaying Channel. IEEE Access. 8. 104127–104138. 24 indexed citations

15.

Badrudduza, A. S. M., S. M. Riazul Islam, Imran Shafique Ansari, et al.. (2020). Secrecy Performance Analysis of Mixed Hyper-Gamma and Gamma-Gamma Cooperative Relaying System. IEEE Access. 8. 131273–131285. 21 indexed citations

16.

Islam, S. M. Riazul, et al.. (2020). Milled Microchannel-Assisted Open D-Channel Photonic Crystal Fiber Plasmonic Biosensor. IEEE Access. 9. 2924–2933. 25 indexed citations

17.

Nkenyereye, Lewis, et al.. (2020). Auto-Colorization of Historical Images Using Deep Convolutional Neural Networks. Mathematics. 8(12). 2258–2258. 17 indexed citations

18.

Singla, Jimmy, Lewis Nkenyereye, Sudan Jha, et al.. (2020). Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives. IEEE Access. 8. 228049–228069. 125 indexed citations

19.

Nkenyereye, Lionel, Lionel Nkenyereye, S. M. Riazul Islam, et al.. (2019). Software-Defined Network-Based Vehicular Networks: A Position Paper on Their Modeling and Implementation. Sensors. 19(17). 3788–3788. 28 indexed citations

20.

Nkenyereye, Lionel, Lewis Nkenyereye, S. M. Riazul Islam, et al.. (2019). Software Defined Network-Based Multi-Access Edge Framework for Vehicular Networks. IEEE Access. 8. 4220–4234. 35 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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