Research
intelligent risk assessment, decision analysis, Bayesian statistical methods, probability, project risk
Interests
He is interested in intelligent risk assessment and decision analysis using knowledge and data. Typically this involves analysing and predicting the probabilities of unknown events using Bayesian statistical methods including causal, probabilistic models (Bayesian networks). In addition to working on theoretical and algorithmic foundations, this work covers a wide range of application domains such as: medical analytics, legal reasoning, embedded software, operational risk in finance, systems and design reliability (including software), project risk, commercial risk, decision support, cost benefit analysis, AI and personalisation, machine learning, legal argumentation, cyber security and football prediction.
Publications

Publications of specific relevance to Applied Data Science
2020
Fenton N,
Osman M, Mclachlan S and
Neil M (2020).
COVID-19 infection and death rates: the need to incorporate causal explanations for the data and avoid bias in testing. Taylor & Francis (Routledge) Journal of Risk Research 10.1080/13669877.2020.17563812019
Neil M,
Fenton N, Lagnado D and Gill RD (2019).
Modelling competing legal arguments using Bayesian model comparison and averaging. Artificial Intelligence and Law vol. 27, (4) 403-430.
10.1007/s10506-019-09250-3
Wang J,
Neil M and
Fenton N (2019).
A Bayesian network approach for cybersecurity risk assessment implementing and extending the FAIR model. Elsevier Computers and Security vol. 89,
10.1016/j.cose.2019.101659
Fenton N, Lagnado D, Dahlman C and
Neil M (2019).
The Opportunity Prior: A proof-based prior for criminal cases. Oxford University Press (Oup) Law, Probability and Risk 10.1093/lpr/mgz007
FENTON NE,
NEIL M and NOGUCHI T (2019).
An extension to the noisy-OR function to resolve the ‘explaining away’ deficiency for practical Bayesian network problem. Institute of Electrical and Electronics Engineers Ieee Transactions On Knowledge and Data Engineering 10.1109/TKDE.2019.28916802018
FENTON NE, NOGUCHI T and
NEIL M (2018).
Addressing the Practical Limitations of Noisy-OR using Conditional Inter-causal Anti-Correlation with Ranked Nodes. Institute of Electrical and Electronics Engineers Ieee Transactions On Knowledge and Data Engineering 10.1109/TKDE.2018.2873314
FENTON NE and
NEIL M (2018).
Are lawnmowers a greater risk than terrorists?2017

Morrison GS, Kaye DH, Balding DJ, Taylor D, Dawid P, Aitken CGG, Gittelson S, Zadora G, Robertson B, Willis S, Pope S,
Neil M, Martire KA, Hepler A, Gill RD, Jamieson A, de Zoete J, Ostrum RB and Caliebe A (2017).
A comment on the PCAST report: Skip the “match”/“non-match” stage. Forensic Science International vol. 272, e7-e9.
10.1016/j.forsciint.2016.10.0182016
2015
2014
Fenton N, Lagnado D, Hsu A, Berger D and
Neil M (2014).
Response to on the use of the likelihood ratio for forensic evaluation: response to Fenton et al.. Sci Justice vol. 54, (4) 319-320.
10.1016/j.scijus.2014.05.005
Fenton NE and
Neil M (2014).
Decision Support Software for Probabilistic Risk Assessment Using Bayesian Networks. Ieee Explore Ieee Software vol. 31, (2) 21-26.
10.1109/MS.2014.32
Zhou Y,
Fenton N and
Neil M (2014).
Bayesian network approach to multinomial parameter learning using data and expert judgments. Elsevier/Science Direct International Journal of Approximate Reasoning vol. 55, 1252-1268.
10.1016/j.ijar.2014.02.008
Fenton N, Berger D, Lagnado D,
Neil M and Hsu A (2014).
When 'neutral' evidence still has probative value (with implications from the Barry George Case). Science and Justice vol. 54, (4) 274-287.
10.1016/j.scijus.2013.07.002
Zhou Y,
Fenton N and
Neil M (2014).
An extended MPL-C model for Bayesian network parameter learning with exterior constraints. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformat vol. 8754, 581-596.
10.1007/978-3-319-11433-0_382013
Fenton NE,
Neil M and Hsu A (2013).
Calculating and understanding the value of any type of match evidence when there are potential testing errors. Springer (Part of Springer Nature) Artificial Intelligence and Law vol. 22, (1) 1-28.
10.1007/s10506-013-9147-x
FENTON NE,
Neil M and Lagnado D (2013).
A General Structure for Legal Arguments About Evidence Using Bayesian Networks. Wiley Online Library Cognitive Science vol. 37, (1) 61-102.
10.1111/cogs.120042012
Neil M, Chen X and
Fenton NE (2012).
Optimizing the Calculation of Conditional Probability Tables in Hybrid Bayesian Networks using Binary Factorization. Ieee Ieee Transactions On Knowledge and Data Engineering vol. 7, (24) 1306-1312.
10.1109/TKDE.2011.87
Neil M and Marquez D (2012).
Availability modelling of repairable systems using Bayesian networks. Elsevier/Science Direct Engineering Applications of Artificial Intelligence vol. 25, (4) 698-704.
10.1016/j.engappai.2010.06.003
FENTON NE and
Neil M (2012).
Risk Assessment with Bayesian Networks. Crc Press 2011
FENTON NE and
Neil M (2011).
Avoiding Legal Fallacies in Practice Using Bayesian Networks. Australian Journal of Legal Philosophy vol. 36, 114-150.
FENTON NE and
Neil M (2011).
The use of Bayes' and causal modelling in decision making, uncertainty and risk. Upgrade, The Journal of Cepis (Council of European Professional Informatics Societies) vol. 12, (5) 10-21.
2010
Neil M, Marquez D and
Fenton N (2010).
Improved Reliability Modeling using Bayesian Networks and Dynamic Discretization. Journal of Reliability Engineering and System Safety vol. 95, (4) 412-425.
10.1016/j.ress.2009.11.0122009

Hearty P,
Fenton N, Marquez D and
Neil M (2009).
Predicting Project Velocity in XP Using a Learning Dynamic Bayesian Network Model. Ieee T Software Eng vol. 35, (1) 124-137.
10.1109/TSE.2008.76
N Fenton MN and Radli ski (2009).
Software Project and Quality Modelling Using Bayesian Networks. Artificial Intelligence Applications For Improved Software Engineering Development: New Prospects. (Part of The Advances in Inte Information Science Reference.
Neil M and Hager D (2009).
Modeling Operational Risk in Financial Institutions using Hybrid Dynamic Bayesian Networks. Journal of Operational Risk vol. 4, (1) 3-33.
10.21314/JOP.2009.0572008

Marquez D,
Neil M and
Fenton N (2008).
Solving dynamic fault trees using a new hybrid Bayesian network inference algorithm. 2008 Mediterranean Conference On Control and Automation - Conference Proceedings, Med'08 609-614.
10.1109/MED.2008.4602222
Neil M, Tailor M, Marquez D,
Fenton NE and Hearty P (2008).
Modelling dependable systems using hybrid Bayesian networks. Reliability Engineering and System Safety vol. 93, (7) 933-939.
10.1016/j.ress.2007.03.009
FENTON NE,
Neil M and Marquez D (2008).
Using Bayesian Networks to Predict Software Defects and Reliability. Institution of Mechanical Engineers Proceedings of The Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability vol. 222, (4) 701-712.
10.1243/1748006XJRR161
Neil M, Marquez D and
Fenton N (2008).
Using Bayesian Networks to Model the Operational Risk to Information Technology Infrastructure in Financial Institutions. Journal of Financial Transformation vol. 22, 131-138.
2007
Neil M, Tailor M and Marquez D (2007).
Inference in hybrid Bayesian networks using dynamic discretization. Stat Comput vol. 17, (3) 219-233.
10.1007/s11222-007-9018-y
Neil M, Fenton N and Marquez D (2007).
Using Bayesian Networks and Simulation for Data Fusion and Risk Analysis. Nato Science For Peace and Security Series: Information and Communication Security , Editors: Skanata and Byrd DM.
Ios Press, Nieuwe Hemweg 6b, 1013 Bg Amsterdam, The Netherlands
Neil M, Tailor M and Marquez D (2007).
Inference in hybrid Bayesian networks using dynamic discretization. Statistics and Computing vol. 17, 219-233-219-233.

Khodakarami V,
Fenton N and
Neil M (2007).
Project Scheduling: Improved approach to incorporate uncertainty using Bayesian Networks. Project Management Journal vol. 38, 39-49.
10.1177/875697280703800205
Radli ski , Fenton NE, Marquez D and Hearty P (2007).
Empirical Analysis of Software Defect Types. Information Systems Architecture and Technology: Information Technology and Web Engineering: Models, Concepts and Challenges (Pr Oficyna Wydawnicza Politechniki Wroc?Awskiej, Wroc?Aw 
Radli ski ,
Fenton NE,
Neil M and Marquez D (2007).
Improved Decision-Making for Software Managers Using Bayesian Networks.
Fenton NE,
Neil M and Gallan J (2007).
Using Ranked nodes to model qualitative judgements in Bayesian Networks. Ieee Transactions On Knowledge and Data Engineering vol. 19, 1420-1432-1420-1432.

Fenton NE and
Neil M (2007).
Managing Risk in the Modern World: Bayesian Networks and the Applications.
Radli ski ,
Fenton NE,
Neil M and Marquez D (2007).
Modelling Prior Productivity and Defect Rates in a Causal Model for Software Project Risk Assessment. Polish Journal of Environmental Studies vol. 16, (4A) 256-260.
2006
Fenton NE, Radlinski L and
Neil M (2006).
Improved Bayesian Networks for Software Project Risk Assessment Using Dynamic Discretisation. Software Engineering Techniques: Design For Quality (Prceedings of Software Engineering Techniques 2006, Warsaw, Poland, 17-20 O , Editors: Sacha K.
Springer, Boston 10.1007/978-0-387-39388-9_14
Neil M,
FENTON NE, Krause P and Mishra R (2006).
Bayesian networks for software process control. Ieee Transactions On Software Engineering 2005

Fenton NE and
Neil M (2005).
A Critique of Software Defect Prediction Models. Machine Learning Applications in Software Engineering , Editors: Zhang D and JJP T.
World Scientific Publishing Co 2004

Fenton NE and
Neil M (2004).
Combining evidence in risk analysis using Bayesian networks. Safety Critical Systems Newsletter vol. 14, 8-13-8-13.
2003
Neil M, Fenton N, Forey S and Harris R (2003).
Assessing Vehicle Reliability using Bayesian Networks. Global Vehicle Reliability , Editors: Strutt JE and Hall PL.
Professional Engineering Publishing
Neil M,
FENTON NE and Krause P (2003).
Software Quality Prediction Using Bayesian Networks. Software Engineering With Computational Intelligence. Khoshgoftaar, Tm (Ed) Kluwer 2002
2001
Neil M,
Fenton N, Forey S and Harris R (2001).
Using Bayesian belief networks to predict the reliability of military vehicles. Comput Control Eng J vol. 12, (1) 11-20.
10.1049/cce:200101032000
Fenton NE and
Neil M (2000).
The Jury Fallacy and the use of Bayesian nets to simplify probabilistic legal arguments. Mathematics Today (Bulletin of The Ima) vol. 36, (6) 180-187.

Fenton NE and
Neil M (2000).
Bayesian belief nets: a causal model for predicting defect rates and resource requirements. Software Testing and Quality Engineering vol. 2, 48-53-48-53.

Littlewood B, Strigini L, Wright D, Fenton NE and
Neil M (2000).
Bayesian Belief Networks for Safety Assessment of Computer-based Systems. System Performance Evaluation Methodologies and Applications , Editors: Gelenbe E.
Crc Press, Boca Raton
Neil M, Fenton N and Nielsen L (2000).
Building large-scale Bayesian Networks. The Knowledge Engineering Review, 15(3) vol. 15, 257-284-257-284.
10.1017/S02698889000030391999
Fenton NE and
Neil M (1999).
A critique of software defect prediction models. Software Engineering, Ieee Transactions On vol. 25, (5) 675-689.
10.1109/32.815326
Fenton NE and
Neil M (1999).
Software metrics: successes, failures and new directions. Journal of Systems and Software vol. 47, 149-157-149-157.
1998

Fenton NE, Littlewood B,
Neil M, Strigini L, Sutcliffe A and Wright D (1998).
Assessing dependability of safety critical systems using diverse evidence. Iee Proceedings Software vol. 145, 35-39-35-39.

Courtois PJ, Fenton NE, Littlewood B,
Neil M, Strigini L and Wright D (1998).
Examination of bayesian belief network for safety assessment of nuclear computer-based systems.
Fenton NE and
Neil M (1998).
A strategy for improving safety related software engineering standards. Software Engineering, Ieee Transactions On vol. 24, 1002-1013-1002-1013.
Neil M, Ostralenk G, Tobin M and Southworth M (1998).
Lessons from using Z to specify a software tool. Ieee Transactions On Software Engineering vol. 24, 15-23-15-23.
1996

Littlewood B,
Neil M and Ostrolenk G (1996).
Uncertainty in Software-Intensive Systems. High Integrity Systems Journal vol. 1, 407-413-407-413.

Littlewood B,
Neil M and Ostrolenk G (1996).
The Role of Models in Managing Uncertainty of Software-Intensive Systems. Reliability Engineering and System Safety vol. 46, 87-95-87-95.
1995
Neil MD (1995).
Statistical Control of Software Quality. McGraw Hill 1994
Neil MD (1994).
Measurement as an alternative to Bureaucracy for the achievement of Software Quality. Software Quality Journal vol. 3, 65-78-65-78.
Neil MD and Bache RM (1994).
Metrics Analysis. McGraw Hill 1993
Neil MD and Bache RM (1993).
Data Linkage Maps. Journal For Software Maintenance: Research and Practice vol. 5, 223-240-223-240.
1992
Neil MD (1992).
Multivariate Assessment of Software Products. Journal of Software Testing, Verification and Reliability vol. 1, 17-37-17-37.
1990

Bache RM and
Neil M (1990).
Validating Technologies for Certifying Software Products. Proceedings of Ifip Conference On Approving Software Products (Asp-90) North-Holland
Neil MD, Slater D and Cole RJ (1990).
Measures for Maintenance Management: A Case Study. Journal For Software Maintenance: Research and Practice vol. 2, 223-240-223-240.