Martin Neil

7.8k total citations · 2 hit papers
93 papers, 5.0k citations indexed

About

Martin Neil is a scholar working on Artificial Intelligence, Software and Information Systems. According to data from OpenAlex, Martin Neil has authored 93 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 35 papers in Software and 27 papers in Information Systems. Recurrent topics in Martin Neil's work include Bayesian Modeling and Causal Inference (49 papers), Software Reliability and Analysis Research (35 papers) and Software Engineering Research (26 papers). Martin Neil is often cited by papers focused on Bayesian Modeling and Causal Inference (49 papers), Software Reliability and Analysis Research (35 papers) and Software Engineering Research (26 papers). Martin Neil collaborates with scholars based in United Kingdom, Türkiye and China. Martin Neil's co-authors include Norman Fenton, David G. Márquez, Anthony C. Constantinou, Paul Krause, David A. Lagnado, Peter Hearty, William Marsh, Barbaros Yet, Yun Zhou and Magda Osman and has published in prestigious journals such as Trends in Cognitive Sciences, Expert Systems with Applications and IEEE Access.

In The Last Decade

Martin Neil

90 papers receiving 4.6k citations

Hit Papers

A critique of software defect prediction models 1999 2026 2008 2017 1999 2012 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Neil United Kingdom 37 2.0k 1.7k 1.6k 873 575 93 5.0k
Norman Fenton United Kingdom 48 5.6k 2.9× 4.1k 2.4× 2.9k 1.9× 943 1.1× 1.4k 2.4× 186 9.9k
Nozer D. Singpurwalla United States 38 532 0.3× 1.4k 0.8× 740 0.5× 1.7k 2.0× 191 0.3× 178 5.8k
Thomas D. Nielsen Denmark 21 353 0.2× 249 0.1× 1.7k 1.1× 539 0.6× 254 0.4× 73 3.4k
Thomas A. Mazzuchi United States 29 276 0.1× 248 0.1× 500 0.3× 663 0.8× 434 0.8× 233 3.2k
Robert G. Sargent United States 35 312 0.2× 648 0.4× 360 0.2× 326 0.4× 589 1.0× 136 5.2k
Dong‐Ling Xu United Kingdom 48 843 0.4× 173 0.1× 2.8k 1.8× 1.0k 1.2× 271 0.5× 172 8.3k
Averill M. Law United States 29 384 0.2× 513 0.3× 557 0.4× 766 0.9× 1.3k 2.3× 91 8.9k
Hoang Pham United States 40 1.6k 0.8× 4.0k 2.3× 197 0.1× 1.4k 1.6× 391 0.7× 212 6.5k
Naeem Seliya United States 32 2.0k 1.0× 1.5k 0.9× 2.0k 1.3× 53 0.1× 987 1.7× 84 5.0k
Terje Aven Norway 63 464 0.2× 834 0.5× 531 0.3× 6.2k 7.1× 213 0.4× 346 12.9k

Countries citing papers authored by Martin Neil

Since Specialization
Citations

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

Fields of papers citing papers by Martin Neil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Neil

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Neil. A scholar is included among the top collaborators of Martin Neil 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 Martin Neil. Martin Neil 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.
McLachlan, Scott, Evangelia Kyrimi, Kudakwashe Dube, et al.. (2024). Approach and Method for Bayesian Network Modelling: The Case for Pregnancy Outcomes in England and Wales. 604–612. 1 indexed citations
2.
Neil, Martin, et al.. (2021). A causal Bayesian network approach for consumer product safety and risk assessment. Journal of Safety Research. 80. 198–214. 7 indexed citations
3.
Neil, Martin & Norman Fenton. (2021). Bayesian Hypothesis Testing and Hierarchical Modeling of Ivermectin Effectiveness. American Journal of Therapeutics. 28(5). e576–e579. 4 indexed citations
4.
Kyrimi, Evangelia, et al.. (2020). Medical idioms for clinical Bayesian network development. Journal of Biomedical Informatics. 108. 103495–103495. 22 indexed citations
5.
Yet, Barbaros, et al.. (2018). An improved method for solving Hybrid Influence Diagrams. International Journal of Approximate Reasoning. 95. 93–112. 6 indexed citations
6.
Osman, Magda, Norman Fenton, Toby D. Pilditch, David A. Lagnado, & Martin Neil. (2018). Whom Do We Trust on Social Policy Interventions?. Basic and Applied Social Psychology. 40(5). 249–268. 25 indexed citations
7.
Constantinou, Anthony C., Norman Fenton, & Martin Neil. (2016). Integrating expert knowledge with data in Bayesian networks: Preserving data-driven expectations when the expert variables remain unobserved. Expert Systems with Applications. 56. 197–208. 68 indexed citations
8.
Constantinou, Anthony C., Barbaros Yet, Norman Fenton, Martin Neil, & William Marsh. (2015). Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences. Artificial Intelligence in Medicine. 66. 41–52. 14 indexed citations
9.
Zhou, Yun, Norman Fenton, & Martin Neil. (2014). Bayesian network approach to multinomial parameter learning using data and expert judgments. International Journal of Approximate Reasoning. 55(5). 1252–1268. 68 indexed citations
10.
Zhou, Yun, et al.. (2013). Incorporating expert judgement into Bayesian network machine learning. International Joint Conference on Artificial Intelligence. 3249–3250. 4 indexed citations
11.
Fenton, Norman, et al.. (2013). When ‘neutral’ evidence still has probative value (with implications from the Barry George Case). Science & Justice. 54(4). 274–287. 29 indexed citations
12.
Lagnado, David A., Norman Fenton, & Martin Neil. (2012). Legal idioms: a framework for evidential reasoning. 4(1). 46–63. 55 indexed citations
13.
Fenton, Norman & Martin Neil. (2011). Avoiding probabilistic reasoning fallacies in legal practice using Bayesian networks. 36(2011). 114. 27 indexed citations
14.
Fenton, Norman & Martin Neil. (2010). Comparing risks of alternative medical diagnosis using Bayesian arguments. Journal of Biomedical Informatics. 43(4). 485–495. 30 indexed citations
15.
Neil, Martin. (2009). Understanding the human consciousness. Docs.school Publications. 46(6). 237–42.
16.
Neil, Martin & Norman Fenton. (2008). Using Bayesian networks to model the operational risk to information technology infrastructure in financial institutions. Journal of financial transformation. 22. 131–138. 10 indexed citations
17.
Radliński, Łukasz, Norman Fenton, Martin Neil, & David G. Márquez. (2007). Improved decision-making for software managers using Bayesian networks. International Conference on Software Engineering. 13–19. 11 indexed citations
18.
Hearty, Peter, et al.. (2005). Automated population of causal models for improved software risk assessment. 433–434. 3 indexed citations
19.
Neil, Martin, et al.. (2000). Building large-scale Bayesian networks. The Knowledge Engineering Review. 15(3). 257–284. 208 indexed citations
20.
Neil, Martin. (1992). Multivariate Assessment of Software Products.. Software Testing Verification and Reliability. 1. 17–37. 11 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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