Shadman Sakib

656 total citations
27 papers, 186 citations indexed

About

Shadman Sakib is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shadman Sakib has authored 27 papers receiving a total of 186 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shadman Sakib's work include COVID-19 diagnosis using AI (5 papers), AI in cancer detection (4 papers) and Anomaly Detection Techniques and Applications (3 papers). Shadman Sakib is often cited by papers focused on COVID-19 diagnosis using AI (5 papers), AI in cancer detection (4 papers) and Anomaly Detection Techniques and Applications (3 papers). Shadman Sakib collaborates with scholars based in Bangladesh, United States and Japan. Shadman Sakib's co-authors include Khan Md. Hasib, Mohammad Shafiul Alam, Md Rafiqul Islam, Imran Razzak, Md. Abu Bakr Siddique, Tonmoy Hossain, Jubayer Al Mahmud, Md. Saifur Rahman, Syoji Kobashi and Farag Azzedin and has published in prestigious journals such as IEEE Access, Advances in Space Research and Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery.

In The Last Decade

Shadman Sakib

24 papers receiving 177 citations

Peers

Shadman Sakib
Clayton Mellina United States
Abu Kaisar Mohammad Masum Bangladesh
Ivan Donadello Italy
Adham Beykikhoshk Australia
Viera Krešňáková Slovakia
Bihter Daş Türkiye
Eshrag Refaee Saudi Arabia
Samuel Jenkins United States
Nagendra Kumar India
Jan Trienes Germany
Clayton Mellina United States
Shadman Sakib
Citations per year, relative to Shadman Sakib Shadman Sakib (= 1×) peers Clayton Mellina

Countries citing papers authored by Shadman Sakib

Since Specialization
Citations

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

Fields of papers citing papers by Shadman Sakib

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shadman Sakib

This figure shows the co-authorship network connecting the top 25 collaborators of Shadman Sakib. A scholar is included among the top collaborators of Shadman Sakib 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 Shadman Sakib. Shadman Sakib 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.
Sakib, Shadman, et al.. (2025). A Survey on Efficient Vision‐Language Models. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 15(3). 2 indexed citations
2.
Sakib, Shadman, et al.. (2024). Multi-Model Attentional Fusion Ensemble for Accurate Skin Cancer Classification. IEEE Access. 12. 181009–181024. 3 indexed citations
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Sakib, Shadman, et al.. (2023). In-Orbit FPGA reprogramming device for small satellites. Advances in Space Research. 71(11). 4549–4556. 3 indexed citations
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Hasib, Khan Md., et al.. (2023). Depression Detection From Social Networks Data Based on Machine Learning and Deep Learning Techniques: An Interrogative Survey. IEEE Transactions on Computational Social Systems. 10(4). 1568–1586. 68 indexed citations
8.
Sakib, Shadman, et al.. (2022). Performance Analysis of Machine Learning Algorithms in Chronic Kidney Disease Prediction. ArXiv.org. 417–423. 1 indexed citations
9.
Sakib, Shadman, Md. Aminul Islam, & Md. Sahadat Hossain. (2022). Assessment of the Seasonal and Spatial Variation in Shear Strength of High Plasticity Clay on Highway Slopes Using DCP Tests. Geo-Congress 2022. 1967. 524–533.
10.
Hasib, Khan Md., et al.. (2022). COVID-19 Prediction based on Infected Cases and Deaths of Bangladesh using Deep Transfer Learning. 296–302. 16 indexed citations
11.
Sakib, Shadman, et al.. (2022). Event Detection from Cricket Videos Using Video-Based CNN Classification of Umpire Signals. 1–5. 5 indexed citations
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Hasib, Khan Md., et al.. (2021). De Novo Drug Property Prediction using Graph Convolutional Neural Networks. 1–6. 7 indexed citations
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Siddique, Md. Abu Bakr, et al.. (2020). Prediction Of Temperature And Rainfall In Bangladesh Using Long Short Term Memory Recurrent Neural Networks. arXiv (Cornell University). 1–6. 10 indexed citations
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Sakib, Shadman, et al.. (2020). Hand Frame Extraction in Surgical Video Images Using Convolutional Neural Network. 36. 1–5. 3 indexed citations
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Sakib, Shadman, et al.. (2018). Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering. 1–6. 8 indexed citations
19.
Sakib, Shadman, et al.. (2018). A Review of Communications Satellite by Focusing on ‘Bangabandhu Satellite-1’, the First GEO Communications Satellite of Bangladesh. 8(5). 123–128. 1 indexed citations
20.
Sakib, Shadman, et al.. (2018). Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering. Preprints.org. 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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