Ibrahim Habli

3.7k total citations
100 papers, 1.6k citations indexed

About

Ibrahim Habli is a scholar working on Safety, Risk, Reliability and Quality, Software and Artificial Intelligence. According to data from OpenAlex, Ibrahim Habli has authored 100 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Safety, Risk, Reliability and Quality, 29 papers in Software and 25 papers in Artificial Intelligence. Recurrent topics in Ibrahim Habli's work include Safety Systems Engineering in Autonomy (46 papers), Software Reliability and Analysis Research (27 papers) and Risk and Safety Analysis (25 papers). Ibrahim Habli is often cited by papers focused on Safety Systems Engineering in Autonomy (46 papers), Software Reliability and Analysis Research (27 papers) and Risk and Safety Analysis (25 papers). Ibrahim Habli collaborates with scholars based in United Kingdom, United States and Sweden. Ibrahim Habli's co-authors include Tim Kelly, Tom Lawton, Zoë Porter, John McDermid, Mark Sujan, Yan Jia, Richard Hawkins, Ganesh Pai, Ewen Denney and Richard Baker and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Software Engineering and Artificial Intelligence.

In The Last Decade

Ibrahim Habli

93 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ibrahim Habli United Kingdom 22 537 411 398 286 264 100 1.6k
Tim Kelly United Kingdom 23 1.1k 2.1× 868 2.1× 387 1.0× 7 0.0× 552 2.1× 110 1.8k
Matthew L. Bolton United States 18 245 0.5× 151 0.4× 161 0.4× 7 0.0× 146 0.6× 88 1.0k
Ellen J. Bass United States 21 210 0.4× 137 0.3× 182 0.5× 5 0.0× 94 0.4× 173 1.7k
William Marsh United Kingdom 20 37 0.1× 263 0.6× 279 0.7× 34 0.1× 95 0.4× 71 1.2k
Dominic Furniss United Kingdom 22 23 0.0× 14 0.0× 132 0.3× 85 0.3× 93 0.4× 79 1.5k
Barry Kirwan United Kingdom 31 467 0.9× 57 0.1× 173 0.4× 3 0.0× 2.1k 8.0× 97 3.9k
Zoie Shui-Yee Wong Japan 19 48 0.1× 10 0.0× 227 0.6× 159 0.6× 73 0.3× 73 1.4k
Fadel M. Megahed United States 24 100 0.2× 4 0.0× 274 0.7× 68 0.2× 464 1.8× 71 2.1k
William H. Maisel United States 37 24 0.0× 17 0.0× 175 0.4× 97 0.3× 12 0.0× 76 5.9k
Ângelo Perkusich Brazil 21 48 0.1× 154 0.4× 324 0.8× 15 0.1× 18 0.1× 250 1.5k

Countries citing papers authored by Ibrahim Habli

Since Specialization
Citations

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

Fields of papers citing papers by Ibrahim Habli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ibrahim Habli

This figure shows the co-authorship network connecting the top 25 collaborators of Ibrahim Habli. A scholar is included among the top collaborators of Ibrahim Habli 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 Ibrahim Habli. Ibrahim Habli 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.
Porter, Zoë, et al.. (2025). Unravelling responsibility for AI. SHILAP Revista de lepidopterología. 23. 100124–100124.
2.
Jia, Yan, et al.. (2025). A deployment safety case for AI-assisted prostate cancer diagnosis. Computers in Biology and Medicine. 192(Pt B). 110237–110237. 1 indexed citations
3.
Paterson, Colin, et al.. (2025). Safety assurance of Machine Learning for autonomous systems. Reliability Engineering & System Safety. 264. 111311–111311. 2 indexed citations
4.
Johnson, Owen, Carolyn McCrorie, Teumzghi F Mebrahtu, et al.. (2024). Implementing an artificial intelligence command centre in the NHS: a mixed-methods study. SHILAP Revista de lepidopterología. 12(41). 1–108. 1 indexed citations
5.
6.
Mebrahtu, Teumzghi F, Jonathan Benn, Carolyn McCrorie, et al.. (2023). The impact of hospital command centre on patient flow and data quality: findings from the UK National Health Service. International Journal for Quality in Health Care. 35(4). 2 indexed citations
7.
Porter, Zoë, et al.. (2023). A principles-based ethics assurance argument pattern for AI and autonomous systems. AI and Ethics. 4(2). 593–616. 12 indexed citations
8.
Jia, Yan, et al.. (2022). Assuring the safety of AI-based clinical decision support systems: a case study of the AI Clinician for sepsis treatment. BMJ Health & Care Informatics. 29(1). e100549–e100549. 21 indexed citations
9.
Porter, Zoë, et al.. (2022). Distinguishing two features of accountability for AI technologies. Nature Machine Intelligence. 4(9). 734–736. 9 indexed citations
10.
McCrorie, Carolyn, Jonathan Benn, Ibrahim Habli, et al.. (2022). Evaluating the safety and patient impacts of an artificial intelligence command centre in acute hospital care: a mixed-methods protocol. BMJ Open. 12(3). e054090–e054090. 10 indexed citations
11.
Sujan, Mark & Ibrahim Habli. (2021). Safety cases for digital health innovations: can they work?. BMJ Quality & Safety. 30(12). 1047–1050. 7 indexed citations
12.
Paterson, Colin, et al.. (2020). Assurance Argument Patterns and Processes for Machine Learning in Safety-Related Systems.. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 23–30. 6 indexed citations
13.
McDermid, John, Yan Jia, & Ibrahim Habli. (2019). Towards a Framework for Safety Assurance of Autonomous Systems. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 18 indexed citations
14.
Magrabi, Farah, Ibrahim Habli, Mark Sujan, et al.. (2019). Why is it so difficult to govern mobile apps in healthcare?. BMJ Health & Care Informatics. 26(1). e100006–e100006. 36 indexed citations
15.
Jia, Yan, Tom Lawton, Sean White, & Ibrahim Habli. (2019). Developing a Safety Case for Electronic Prescribing. Studies in health technology and informatics. 264. 629–633.
16.
Sujan, Mark, Dominic Furniss, Howard Grundy, et al.. (2019). Human factors challenges for the safe use of artificial intelligence in patient care. BMJ Health & Care Informatics. 26(1). e100081–e100081. 74 indexed citations
17.
Burton, Simon, et al.. (2019). Mind the gaps: Assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. Artificial Intelligence. 279. 103201–103201. 91 indexed citations
18.
Călinescu, Radu, Danny Weyns, Simos Gerasimou, et al.. (2018). [Journal First] ENTRUST: Engineering Trustworthy Self-Adaptive Software with Dynamic Assurance Cases. International Conference on Software Engineering. 1 indexed citations
19.
Denney, Ewen, Ganesh Pai, & Ibrahim Habli. (2015). Dynamic Safety Cases for Through-Life Safety Assurance. 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering. 587–590. 40 indexed citations
20.
Denney, Ewen, Ibrahim Habli, Tim Kelly, John Knight, & Ganesh Pai. (2013). Proceedings of the 1st International Workshop on Assurance Cases for Software-Intensive Systems. International Conference on Software Engineering. 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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