Mobarakol Islam

1.7k total citations
45 papers, 370 citations indexed

About

Mobarakol Islam is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Mobarakol Islam has authored 45 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 11 papers in Biomedical Engineering. Recurrent topics in Mobarakol Islam's work include Domain Adaptation and Few-Shot Learning (11 papers), Multimodal Machine Learning Applications (8 papers) and Surgical Simulation and Training (7 papers). Mobarakol Islam is often cited by papers focused on Domain Adaptation and Few-Shot Learning (11 papers), Multimodal Machine Learning Applications (8 papers) and Surgical Simulation and Training (7 papers). Mobarakol Islam collaborates with scholars based in United Kingdom, Hong Kong and Singapore. Mobarakol Islam's co-authors include Hongliang Ren, Mengya Xu, Chwee Ming Lim, Dulani Meedeniya, Indika Perera, Vibashan VS, Long Bai, An Wang, Weng Kin Wong and Venkatesh Srinivasan and has published in prestigious journals such as IEEE Access, IEEE Transactions on Medical Imaging and Medical Physics.

In The Last Decade

Mobarakol Islam

40 papers receiving 362 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mobarakol Islam United Kingdom 12 122 121 105 96 51 45 370
Nandhini Santhanam Germany 3 175 1.4× 79 0.7× 205 2.0× 94 1.0× 22 0.4× 4 519
Zelong Liu China 10 104 0.9× 62 0.5× 141 1.3× 69 0.7× 20 0.4× 27 355
Kim Eun Hee Germany 5 180 1.5× 82 0.7× 201 1.9× 77 0.8× 23 0.5× 25 496
D. R. Sarvamangala India 3 194 1.6× 133 1.1× 207 2.0× 70 0.7× 18 0.4× 5 541
Mahboubeh Jannesari Germany 3 234 1.9× 108 0.9× 245 2.3× 79 0.8× 22 0.4× 7 510
Laurent Massoptier Italy 11 142 1.2× 263 2.2× 252 2.4× 128 1.3× 54 1.1× 23 543
Biswajit Jena India 10 127 1.0× 129 1.1× 202 1.9× 46 0.5× 12 0.2× 21 431
Yeşim Eroğlu Türkiye 9 126 1.0× 66 0.5× 131 1.2× 31 0.3× 33 0.6× 23 343
Arnaldo Mayer Israel 13 107 0.9× 256 2.1× 222 2.1× 100 1.0× 18 0.4× 45 584
Neeraj Sharma India 13 126 1.0× 72 0.6× 208 2.0× 91 0.9× 29 0.6× 32 542

Countries citing papers authored by Mobarakol Islam

Since Specialization
Citations

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

Fields of papers citing papers by Mobarakol Islam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mobarakol Islam

This figure shows the co-authorship network connecting the top 25 collaborators of Mobarakol Islam. A scholar is included among the top collaborators of Mobarakol 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 Mobarakol Islam. Mobarakol Islam 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.
Zhao, Shifang, Long Bai, Kun Yuan, et al.. (2025). Rethinking data imbalance in class incremental surgical instrument segmentation. Medical Image Analysis. 105. 103728–103728.
2.
Bai, Long, Zhongliang Jiang, Mobarakol Islam, et al.. (2025). Multimodal graph representation learning for robust surgical workflow recognition with adversarial feature disentanglement. Information Fusion. 123. 103290–103290.
3.
Bai, Long, et al.. (2024). Surgical-VQLA++: Adversarial contrastive learning for calibrated robust visual question-localized answering in robotic surgery. Information Fusion. 113. 102602–102602. 7 indexed citations
4.
Bai, Long, Jie Wang, Huxin Gao, et al.. (2024). OSSAR: Towards Open-Set Surgical Activity Recognition in Robot-assisted Surgery. 14622–14629. 3 indexed citations
5.
6.
Islam, Mobarakol, Danyal Z. Khan, Simon C. Williams, et al.. (2024). PitSurgRT: real-time localization of critical anatomical structures in endoscopic pituitary surgery. International Journal of Computer Assisted Radiology and Surgery. 19(6). 1053–1060. 7 indexed citations
7.
Islam, Mobarakol, et al.. (2024). A Novel Few-Shot ML Approach for Intrusion Detection in IoT. Arabian Journal for Science and Engineering. 50(10). 7765–7779. 2 indexed citations
8.
Islam, Mobarakol, et al.. (2024). Surgical-DINO: adapter learning of foundation models for depth estimation in endoscopic surgery. International Journal of Computer Assisted Radiology and Surgery. 19(6). 1013–1020. 17 indexed citations
9.
Chen, Kexin, Tao You, Mobarakol Islam, et al.. (2024). LLM-Assisted Multi-Teacher Continual Learning for Visual Question Answering in Robotic Surgery. 10772–10778. 8 indexed citations
10.
Bano, Sophia, et al.. (2024). Surgical-DeSAM: decoupling SAM for instrument segmentation in robotic surgery. International Journal of Computer Assisted Radiology and Surgery. 19(7). 1267–1271. 4 indexed citations
11.
Wang, Kaifeng, Dongsheng Xie, Xue Li, et al.. (2024). Dual‐stage semantic segmentation of endoscopic surgical instruments. Medical Physics. 51(12). 9125–9137.
12.
Islam, Mobarakol, et al.. (2023). Image-guidance in endoscopic pituitary surgery: an in-silico study of errors involved in tracker-based techniques. Frontiers in Surgery. 10. 1222859–1222859. 2 indexed citations
13.
Islam, Mobarakol, et al.. (2023). Paced-curriculum distillation with prediction and label uncertainty for image segmentation. International Journal of Computer Assisted Radiology and Surgery. 18(10). 1875–1883. 4 indexed citations
14.
Islam, Mobarakol, et al.. (2023). Task-aware asynchronous multi-task model with class incremental contrastive learning for surgical scene understanding. International Journal of Computer Assisted Radiology and Surgery. 18(5). 921–928. 2 indexed citations
15.
Kamnitsas, Konstantinos, Lisa M. Koch, Mobarakol Islam, et al.. (2022). Domain Adaptation and Representation Transfer. Lecture notes in computer science. 1 indexed citations
16.
Islam, Mobarakol, et al.. (2021). Glioblastoma multiforme prognosis: MRI missing modality generation, segmentation and radiogenomic survival prediction. Computerized Medical Imaging and Graphics. 91. 101906–101906. 31 indexed citations
17.
Islam, Mobarakol, Vibashan VS, Angela An Qi See, et al.. (2021). Identifying risk factors of intracerebral hemorrhage stability using explainable attention model. Medical & Biological Engineering & Computing. 60(2). 337–348. 5 indexed citations
18.
Islam, Mobarakol, Vibashan VS, Chwee Ming Lim, & Hongliang Ren. (2020). ST-MTL: Spatio-Temporal multitask learning model to predict scanpath while tracking instruments in robotic surgery. Medical Image Analysis. 67. 101837–101837. 24 indexed citations
19.
Islam, Mobarakol, et al.. (2020). Ultrasound needle segmentation and trajectory prediction using excitation network. International Journal of Computer Assisted Radiology and Surgery. 15(3). 437–443. 30 indexed citations
20.
Islam, Mobarakol, et al.. (2011). Training neural network with chaotic learning rate. 6. 781–785. 6 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Nandhini Santhanam Breakdown of academic impact, for papers by Zelong Liu Breakdown of academic impact, for papers by Kim Eun Hee Breakdown of academic impact, for papers by D. R. Sarvamangala Breakdown of academic impact, for papers by Mahboubeh Jannesari Breakdown of academic impact, for papers by Laurent Massoptier Breakdown of academic impact, for papers by Biswajit Jena Breakdown of academic impact, for papers by Yeşim Eroğlu Breakdown of academic impact, for papers by Arnaldo Mayer Breakdown of academic impact, for papers by Neeraj Sharma
Rankless by CCL
2026