Michael C. Fu

914 total citations · 2 hit papers
21 papers, 481 citations indexed

About

Michael C. Fu is a scholar working on Information Systems, Computer Networks and Communications and Software. According to data from OpenAlex, Michael C. Fu has authored 21 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Information Systems, 9 papers in Computer Networks and Communications and 8 papers in Software. Recurrent topics in Michael C. Fu's work include Software Engineering Research (11 papers), Software Reliability and Analysis Research (7 papers) and Software System Performance and Reliability (5 papers). Michael C. Fu is often cited by papers focused on Software Engineering Research (11 papers), Software Reliability and Analysis Research (7 papers) and Software System Performance and Reliability (5 papers). Michael C. Fu collaborates with scholars based in Australia, United States and China. Michael C. Fu's co-authors include Chakkrit Tantithamthavorn, Van Nguyen, Trung Le, Dinh Phung, E. William East, Jirayus Jiarpakdee, Patanamon Thongtanunam, John Grundy, Chetan Arora and Alexey Ignatiev and has published in prestigious journals such as IEEE Access, IEEE Transactions on Software Engineering and Journal of Systems and Software.

In The Last Decade

Michael C. Fu

18 papers receiving 469 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.

LineVul

2022 165 citations Michael C. Fu, Chakkrit Tantithamthavorn profile →
VulRepair: a T5-based automated software vulnerability repair

2022 107 citations Michael C. Fu, Chakkrit Tantithamthavorn et al. profile →

Peers

Michael C. Fu

IS

SOFTW

SP

AI

CNC

Byron J. Williams United States

Zhiyi Ma China

Csaba Nagy Switzerland

Amani S. Ibrahim Australia

Pedro Martins Portugal

Mário Jino Brazil

Sigrid Eldh Sweden

Philippe Charland Canada

Lin Shi China

Mustafa Hammad Bahrain

Byron J. Williams United States

Michael C. Fu

356 ×1.1

IS

177 ×0.8

SOFTW

81 ×0.6

SP

101 ×0.9

AI

110 ×1.0

CNC

Citations per year, relative to Michael C. Fu Michael C. Fu (= 1×) peers Byron J. Williams

Countries citing papers authored by Michael C. Fu

Since Specialization

Citations

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

Fields of papers citing papers by Michael C. Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael C. Fu. 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 Michael C. Fu. The network helps show where Michael C. Fu may publish in the future.

Co-authorship network of co-authors of Michael C. Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Michael C. Fu. A scholar is included among the top collaborators of Michael C. Fu 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 Michael C. Fu. Michael C. Fu 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.

Fu, Michael C., et al.. (2025). AI for DevSecOps: A Landscape and Future Opportunities. ACM Transactions on Software Engineering and Methodology. 34(4). 1–61. 4 indexed citations

2.

Fu, Michael C., et al.. (2025). RAGVA: Engineering retrieval augmented generation-based virtual assistants in practice. Journal of Systems and Software. 226. 112436–112436. 4 indexed citations

3.

Fu, Michael C., Chakkrit Tantithamthavorn, & Trung Le. (2025). DAViT: A Domain-Adapted Vision Transformer for Automated Pneumonia Detection and Explanation Using Chest X-Ray Images. IEEE Access. 13. 103033–103044.

4.

Fu, Michael C., et al.. (2025). A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection. 161–168.

5.

Fu, Michael C., et al.. (2024). A Formal Explainer for Just-In-Time Defect Predictions. ACM Transactions on Software Engineering and Methodology. 33(7). 1–31. 1 indexed citations

6.

Fu, Michael C., Chakkrit Tantithamthavorn, Trung Le, et al.. (2023). AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities. Empirical Software Engineering. 29(1). 24 indexed citations

7.

Fu, Michael C., Chakkrit Tantithamthavorn, Van Nguyen, & Trung Le. (2023). ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We?. 632–636. 39 indexed citations

8.

Fu, Michael C.. (2023). Toward More Effective Deep Learning-based Automated Software Vulnerability Prediction, Classification, and Repair. 208–212.

9.

Fu, Michael C., Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung, & Trung Le. (2023). Vision Transformer Inspired Automated Vulnerability Repair. ACM Transactions on Software Engineering and Methodology. 33(3). 1–29. 11 indexed citations

10.

Fu, Michael C., Van Nguyen, Chakkrit Tantithamthavorn, Trung Le, & Dinh Phung. (2023). VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types. IEEE Transactions on Software Engineering. 49(10). 4550–4565. 22 indexed citations

11.

Fu, Michael C. & Chakkrit Tantithamthavorn. (2022). LineVul. 608–620. 165 indexed citations breakdown →

12.

Fu, Michael C., Chakkrit Tantithamthavorn, Trung Le, Van Nguyen, & Dinh Phung. (2022). VulRepair: a T5-based automated software vulnerability repair. 935–947. 107 indexed citations breakdown →

13.

Fu, Michael C. & Chakkrit Tantithamthavorn. (2022). GPT2SP: A Transformer-Based Agile Story Point Estimation Approach. IEEE Transactions on Software Engineering. 49(2). 611–625. 40 indexed citations

14.

Tantithamthavorn, Chakkrit, et al.. (2021). PyExplainer: Explaining the Predictions of Just-In-Time Defect Models. 407–418. 34 indexed citations

15.

Fu, Michael C., et al.. (2016). Cost-Efficient Parallel RSA Decryption with Integrated GPGPU and OpenCL. 30. 597–602. 1 indexed citations

16.

Eric, C., Michael C. Fu, & Jean Walrand. (2004). Proactive resource provisioning. Computer Communications. 27(12). 1174–1182. 1 indexed citations

17.

Fu, Michael C. & E. William East. (1999). The Virtual Design Review. Computer-Aided Civil and Infrastructure Engineering. 14(1). 25–35. 13 indexed citations

18.

East, E. William & Michael C. Fu. (1996). Abstracting Lessons Learned from Design Reviews. Journal of Computing in Civil Engineering. 10(4). 267–275. 10 indexed citations

19.

East, E. William, et al.. (1995). The Reviewer's Assistant System: System Design Analysis and Description.. 3 indexed citations

20.

Fu, Michael C., Jian-Qiang Hu, & Rakesh Nagi. (1993). Gradient Estimation for Queues with Non-identical Servers. Digital Repository at the University of Maryland (University of Maryland College Park). 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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