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Institute of Applied Data Science

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Professor Martin Neil

Martin Neil

Professor of Computer Science and Statistics

Department School of Electronic Engineering and Computer Science
 School of Electronic Engineering and Computer Science
Tel: +44 (0)20 7882 3400 

www.eecs.qmul.ac.uk/~martin/

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

Kyrimi E, Raniere Neves M, Mclachlan S, Neil M, Marsh W and Fenton N (2020). Medical idioms for clinical Bayesian network development. Elsevier  Journal of Biomedical Informatics  10.1016/j.jbi.2020.103495
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  10.1080/13669877.2020.1756381
Fenton N, Neil M and Constantinou A (2020). The Book of Why: The New Science of Cause and Effect, Judea Pearl, Dana Mackenzie, Basic Books (2018). Elsevier Bv  Artificial Intelligence  vol. 284, 103286-103286. 10.1016/j.artint.2020.103286

2019

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
Neil M, Fenton N, Osman M and Lagnado D (2019). Causality, the critical but often ignored component guiding us through a world of uncertainties in risk assessment. Journal of Risk Research  10.1080/13669877.2019.1604564
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.2019.2891680
Fenton N, Neil M, Yet B and Lagnado D (2019). Analyzing the Simonshaven Case Using Bayesian Networks. Topics in Cognitive Science  10.1111/tops.12417

2018

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
OSMAN M, FENTON NE, Pilditch T, Lagnado D and NEIL M (2018). Who do we trust on social policy interventions. Basic and Applied Social Psychology  10.1080/01973533.2018.1469986
Osman M, Fenton N, Pilditch T, Lagnado D and Neil M (2018). Whom Do We Trust on Social Policy Interventions? Basic and Applied Social Psychology  10.1080/01973533.2018.1469986
YET B, NEIL M, FENTON N, CONSTANTINOU AC and DEMENTIEV E (2018). An Improved Method for Solving Hybrid Influence Diagrams. Elsevier  International Journal of Approximate Reasoning  10.1016/j.ijar.2018.01.006
FENTON NE and NEIL M (2018). Lawnmowers versus terrorists: A highly misleading view of risk. Royal Statistical Society  Significance  vol. 15, (1) 12-15. 10.1111/j.1740-9713.2018.01104.x
Yet B, Constantinou A, Fenton N and Neil M (2018). Expected Value of Partial Perfect Information in Hybrid Models Using Dynamic Discretization. Ieee Access  vol. 6, 7802-7817. 10.1109/ACCESS.2018.2799527
FENTON NE and NEIL M (2018). Are lawnmowers a greater risk than terrorists?

2017

Neil M and Fenton N (2017). Risk Management Using Bayesian Networks. John Wiley & Sons, Ltd  10.1002/9781118445112.stat07943
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.2016.10.018

2016

Fenton N, Neil M, Lagnado D, William M, Yet B and CONSTANTINOU AC (2016). How to model mutually exclusive events based on independent causal pathways in Bayesian network models. Knowledge-Based Systems  10.1016/j.knosys.2016.09.012
Yet B, CONSTANTINOU AC, Fenton N, Neil M, Luedeling E and Shepherd K (2016). A Bayesian Network Framework for Project Cost, Benefit and Risk Analysis with an Agricultural Development Case Study. Expert Systems With Applications  10.1016/j.eswa.2016.05.005
CONSTANTINOU AC, FENTON N and NEIL M (2016). Integrating expert knowledge with data in Bayesian networks: Preserving data-driven expectations when the expert variables remain unobserved. Expert Systems With Applications  10.1016/j.eswa.2016.02.050
FENTON NE, neil M and Berger D (2016). Bayes and the Law. Annual Review of Statistics and Its Application  vol. 3, 51-77. 10.1146/annurev-statistics-041715-033428

2015

Constantinou AC, Yet B, Fenton N, Neil M and Marsh W (2015). Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences. Elsevier  Artificial Intelligence in Medicine  vol. 66, 41-52. 10.1016/j.artmed.2015.09.002

2014

Lin P, Neil M and Fenton NE (2014). Risk Aggregation in the presence of Discrete Causally Connected Random Variables. Annals of Actuarial Science  vol. 8, (2) 298-319. 10.1017/S1748499514000098
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_38

2013

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
Constantinou AC, Fenton NE and Neil M (2013). Profiting from an inefficient association football gambling market: Prediction, risk and uncertainty using Bayesian networks. Knowledge-Based Systems  vol. 50, 60-86. 10.1016/j.knosys.2013.05.008
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.12004
Fenton N, Berger D, Lagnado D, Neil M and Hsu A (2013). When 'neutral' evidence still has probative value (with implications from the Barry George Case). Science and Justice  10.1016/j.scijus.2013.07.002

2012

Constantinou A, FENTON NE and Neil M (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Elsevier  Knowledge Based Systems  vol. 36, 322-339. 10.1016/j.knosys.2012.07.008
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, Lagnado D and Neil M (2012). Legal idioms: a framework for evidential reasoning. Taylor & Francis Online  Argument and Computation  vol. 4, (1) 46-63. 10.1080/19462166.2012.682656
FENTON NE and Neil M (2012). Risk Assessment with Bayesian Networks. Crc Press 
Fenton N and Neil M (2012). Risk assessment and decision analysis with bayesian networks. 10.1201/b21982

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

Fenton N and Neil M (2010). Comparing risks of alternative medical diagnosis using Bayesian arguments. J Biomed Inform  vol. 43, (4) 485-495. 10.1016/j.jbi.2010.02.004
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.2009.11.012

2009

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.2009.057

2008

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
Fenton N, Neil M, Marsh W, Hearty P, Radlinski L and Krause P (2008). On the effectiveness of early life cycle defect prediction with Bayesian Nets. Empirical Software Engineering  vol. 13, (5) 499-537. 10.1007/s10664-008-9072-x
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

Fenton NE, Neil M and Caballero JG (2007). Using ranked nodes to model qualitative judgments in Bayesian Networks. Ieee T Knowl Data En  vol. 19, (10) 1420-1432. 10.1109/TKDE.2007.1068
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 NE, Hearty P, Marquez D and Tailor M (2007). Modelling dependable systems using hybrid Bayesian networks. Reliability Engineering & System Safety  vol. 93, 1-19. 10.1016/j.ress.2007.03.009
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.
Fenton N, Neil M, Marsh W, Hearty P, Marquez D, Krause P and Mishra R (2007). Predicting software defects in varying development lifecycles using Bayesian nets. Inform Software Tech  vol. 49, (1) 32-43. 10.1016/j.infsof.2006.09.001
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 N and Neil M (2006). Expert elicitation for reliable system design - Comment. Stat Sci  vol. 21, (4) 451-453. 10.1214/088342306000000510
Fenton N and Neil M (2006). Comment: Expert elicitation for reliable system design. Statistical Science  vol. 21, (4) 451-453. 10.1214/088342306000000529
Joseph A, Fenton NE and Neil M (2006). Predicting football results using Bayesian nets and other machine learning techniques. Knowl-Based Syst  vol. 19, (7) 544-553. 10.1016/j.knosys.2006.04.011
Neil M and FENTON NE (2006). AgenaRisk. Agena Ltd 
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 
Fenton NE and Neil M (2006). Expert Elicitation for Reliable System Design. Statistical Science  vol. 21, 451-453-451-453. 10.1214/088342306000000529

2005

Neil M, Fenton N and Tailor M (2005). Using Bayesian networks to model expected and unexpected operational losses. Risk Anal  vol. 25, (4) 963-972. 10.1111/j.1539-6924.2005.00641.x
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 and FENTON NE (2003). Improved Programme Selection.
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

Fenton N, Krause P and Neil M (2002). Software measurement: Uncertainty and causal modeling. Ieee Software  vol. 19, (4) 116-+. 10.1109/MS.2002.1020298
Fenton NE, Krause P and Neil M (2002). Probabilistic Modelling for Software Quality Control. Journal of Applied Non-Classical Logics  vol. 12, (2) 173-188. 10.3166/jancl.12.173-188

2001

Fenton N and Neil M (2001). Making decisions: using Bayesian nets and MCDA. Knowl-Based Syst  vol. 14, (7) 307-325. 10.1016/S0950-7051(00)00071-X
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:20010103

2000

Neil M, Fenton N and Nielsen L (2000). Building large-scale Bayesian networks. Knowl Eng Rev  vol. 15, (3) 257-284. 10.1017/S0269888900003039
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/S0269888900003039

1999

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.

Grants

Grants of specific relevance to Applied Data Science
PAMBAYESIAN: PAtient Managed decision-support using Bayesian networks
Fenton NE, Collier DJ, Neil M, Patel A, Hitman GA, Humby FC, Huda MSB, Brown VT, Curzon P, Alomainy A, Morrissey D and Marsh W
£1,538,497 Engineering and Physical Sciences Research Council (30-06-2017 - 31-12-2020)
Summary