Professor Martin Neil
Professor of Computer Science and Statistics
School of Electronic Engineering and Computer Science
School of Electronic Engineering and Computer Science
Tel: +44 (0)20 7882 3400
m.neil@qmul.ac.uk
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 Science2020
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.2020.103495Fenton 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 10.1080/13669877.2020.1756381Fenton 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.2020.1032862019
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/s10506-019-09250-3Wang 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.2019.101659Fenton 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/mgz007Neil 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 10.1080/13669877.2019.1604564FENTON 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.2019.2891680Fenton N, Neil M, Yet B and Lagnado D (2019). Analyzing the Simonshaven Case Using Bayesian Networks. Topics in Cognitive Science 10.1111/tops.124172018
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.2018.2873314OSMAN M, FENTON NE, Pilditch T, Lagnado D and NEIL M (2018). Who do we trust on social policy interventions. Basic and Applied Social Psychology 10.1080/01973533.2018.1469986Osman M, Fenton N, Pilditch T, Lagnado D and Neil M (2018). Whom Do We Trust on Social Policy Interventions? Basic and Applied Social Psychology 10.1080/01973533.2018.1469986YET 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.2018.01.006FENTON 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.xYet 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.2018.27995272017
Neil M and Fenton N (2017). Risk Management Using Bayesian Networks. John Wiley & Sons, Ltd 10.1002/9781118445112.stat07943Morrison 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
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.2016.09.012Yet 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.2016.05.005CONSTANTINOU 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.2016.02.050FENTON 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-041715-0334282015
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.2015.09.0022014
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/S1748499514000098Fenton 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.2014.05.005Fenton 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.2014.32Zhou 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.2014.02.008Fenton 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.2013.07.002Zhou 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-xConstantinou 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.2013.05.008FENTON 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.12004Fenton 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.2013.07.0022012
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.2012.07.008Neil 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.2011.87Neil 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.2010.06.003FENTON 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. 10.1080/19462166.2012.682656Fenton N and Neil M (2012). Risk assessment and decision analysis with bayesian networks. 10.1201/b219822011
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.2010.02.004Neil 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.2008.76N 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.2008.4602222Fenton 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-xNeil 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.2007.03.009FENTON 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. 10.1243/1748006XJRR161Neil 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.2007.1068Neil 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-yNeil 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.2007.03.009Neil 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.2006.09.001Khodakarami V, Fenton N and Neil M (2007). Project Scheduling: Improved approach to incorporate uncertainty using Bayesian Networks. Project Management Journal vol. 38, 39-49. 10.1177/875697280703800205Radli 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. 10.1214/088342306000000510Fenton N and Neil M (2006). Comment: Expert elicitation for reliable system design. Statistical Science vol. 21, (4) 451-453. 10.1214/088342306000000529Joseph 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.2006.04.011Fenton 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_14Neil 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. 10.1214/0883423060000005292005
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.xFenton 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
Fenton N, Krause P and Neil M (2002). Software measurement: Uncertainty and causal modeling. Ieee Software vol. 19, (4) 116-+. 10.1109/MS.2002.1020298Fenton 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.12.173-1882001
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-XNeil 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
Neil M, Fenton N and Nielsen L (2000). Building large-scale Bayesian networks. Knowl Eng Rev vol. 15, (3) 257-284. 10.1017/S0269888900003039Fenton 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. 10.1109/32.815326Fenton 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. 