Md. Mostafizer Rahman

1.7k total citations · 1 hit paper
28 papers, 842 citations indexed

About

Md. Mostafizer Rahman is a scholar working on Information Systems, Artificial Intelligence and Software. According to data from OpenAlex, Md. Mostafizer Rahman has authored 28 papers receiving a total of 842 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Information Systems, 10 papers in Artificial Intelligence and 10 papers in Software. Recurrent topics in Md. Mostafizer Rahman's work include Software Engineering Research (12 papers), Software Testing and Debugging Techniques (9 papers) and Online Learning and Analytics (7 papers). Md. Mostafizer Rahman is often cited by papers focused on Software Engineering Research (12 papers), Software Testing and Debugging Techniques (9 papers) and Online Learning and Analytics (7 papers). Md. Mostafizer Rahman collaborates with scholars based in Japan, Bangladesh and United States. Md. Mostafizer Rahman's co-authors include Yutaka Watanobe, Keita Nakamura, R. Uday Kiran, Md. Nasim Akhtar, Incheon Paik, Truong Cong Thang, Md. Rashedul Islam, Keitaro Naruse, Md Ashad Alam and Md. Ahsan Habib and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Md. Mostafizer Rahman

24 papers receiving 796 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.

ChatGPT for Education and Research: Opportunities, Threats, and Strategies

2023 496 citations Md. Mostafizer Rahman, Yutaka Watanobe Applied Sciences profile →

Peers

Md. Mostafizer Rahman

AI

HI

CSA

IS

RNMI

Xiaoyuan Yi China

Álvaro Figueira Portugal

Lakshmana Kumar Ramasamy India

David Alonso-Ríos Spain

Konstantinos I. Roumeliotis Greece

Muhammad Wasif Nisar Pakistan

Emily Reif United States

Amir Pouran Ben Veyseh United States

Enis Karaarslan Türkiye

Gagan Bansal United States

Xiaoyuan Yi China

Md. Mostafizer Rahman

538 ×1.5

AI

86 ×0.3

HI

27 ×0.1

CSA

159 ×0.8

IS

29 ×0.4

RNMI

Citations per year, relative to Md. Mostafizer Rahman Md. Mostafizer Rahman (= 1×) peers Xiaoyuan Yi

Countries citing papers authored by Md. Mostafizer Rahman

Since Specialization

Citations

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

Fields of papers citing papers by Md. Mostafizer Rahman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Md. Mostafizer Rahman. 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 Md. Mostafizer Rahman. The network helps show where Md. Mostafizer Rahman may publish in the future.

Co-authorship network of co-authors of Md. Mostafizer Rahman

This figure shows the co-authorship network connecting the top 25 collaborators of Md. Mostafizer Rahman. A scholar is included among the top collaborators of Md. Mostafizer Rahman 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 Md. Mostafizer Rahman. Md. Mostafizer Rahman 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

1.

Hossain, Md. Delwar, et al.. (2025). Identifying Multi-Omics Interactions for Lung Cancer Drug Targets Discovery Using Kernel Machine Regression. Applied Sciences. 15(21). 11506–11506.

2.

Rahman, Md. Mostafizer, et al.. (2025). Integrating Feature Selection and Deep Learning: A Hybrid Approach for Smart Agriculture Applications. Algorithms. 18(4). 222–222.

3.

Rahman, Md. Mostafizer, et al.. (2025). RoBERTa-BiLSTM: A Context-Aware Hybrid Model for Sentiment Analysis. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(6). 3788–3805. 7 indexed citations

4.

Watanobe, Yutaka, et al.. (2025). Source Code Error Understanding Using BERT for Multi-Label Classification. IEEE Access. 13. 3802–3822. 2 indexed citations

5.

Rahman, Md. Mostafizer, et al.. (2024). Big Coding Data: Analysis, Insights, and Applications. IEEE Access. 12. 196010–196026.

6.

Rahman, Md. Mostafizer, et al.. (2024). CommentClass: A Robust Ensemble Machine Learning Model for Comment Classification. International Journal of Computational Intelligence Systems. 17(1). 2 indexed citations

7.

Watanobe, Yutaka, et al.. (2024). Prediction of Students’ Adaptability Using Explainable AI in Educational Machine Learning Models. Applied Sciences. 14(12). 5141–5141. 5 indexed citations

8.

Rahman, Md. Mostafizer, et al.. (2024). Multi-Label Code Error Classification Using CodeT5 and ML-KNN. IEEE Access. 12. 100805–100820. 3 indexed citations

9.

Rahman, Md. Mostafizer, et al.. (2023). Program Repair with Minimal Edits Using CodeT5. 178–184. 5 indexed citations

10.

Rahman, Md. Mostafizer & Yutaka Watanobe. (2023). ChatGPT for Education and Research: Opportunities, Threats, and Strategies. Applied Sciences. 13(9). 5783–5783. 496 indexed citations breakdown →

11.

Rahman, Md. Mostafizer & Yutaka Watanobe. (2023). Multilingual Program Code Classification Using $n$-Layered Bi-LSTM Model With Optimized Hyperparameters. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(2). 1452–1468. 12 indexed citations

12.

Rahman, Md. Mostafizer, et al.. (2022). Impact of Programming Language Skills in Programming Learning. 271–277. 4 indexed citations

13.

Watanobe, Yutaka, et al.. (2022). Identifying algorithm in program code based on structural features using CNN classification model. Applied Intelligence. 53(10). 12210–12236. 18 indexed citations

14.

Watanobe, Yutaka, et al.. (2022). Unknown Object Detection Using a One-Class Support Vector Machine for a Cloud–Robot System. Sensors. 22(4). 1352–1352. 14 indexed citations

15.

Rahman, Md. Mostafizer, Yutaka Watanobe, R. Uday Kiran, Truong Cong Thang, & Incheon Paik. (2021). Challenges and Exit Strategies for Adapting Interactive Online Education Amid the Pandemic and its Aftermath. 595–602. 2 indexed citations

16.

Watanobe, Yutaka, et al.. (2021). Adaptive User Interface for Smart Programming Exercise. 1–7.

17.

Rahman, Md. Mostafizer, Yutaka Watanobe, R. Uday Kiran, Truong Cong Thang, & Incheon Paik. (2021). Impact of Practical Skills on Academic Performance: A Data-Driven Analysis. IEEE Access. 9. 139975–139993. 22 indexed citations

18.

Rahman, Md. Mostafizer, Yutaka Watanobe, & Keita Nakamura. (2020). Source Code Assessment and Classification Based on Estimated Error Probability Using Attentive LSTM Language Model and Its Application in Programming Education. Applied Sciences. 10(8). 2973–2973. 52 indexed citations

19.

Rahman, Md. Mostafizer, Yutaka Watanobe, & Keita Nakamura. (2020). A Neural Network Based Intelligent Support Model for Program Code Completion. Scientific Programming. 2020. 1–18. 26 indexed citations

20.

Rahman, Md. Mostafizer, et al.. (2012). Improvement of K-means clustering algorithm with better initial centroids based on weighted average. 647–650. 38 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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