Dr Anthony Constantinou
Senior Lecturer
Head of the MInDS Research Group
School of Electronic Engineering and Computer Science
Queen Mary University of London
Queen Mary University of London
Research
Causal machine learning, Causal discovery, Decision systems, Bayesian networks, Graphical models, Uncertainty quantification
Interests
My research focuses on causal machine learning for intelligent and autonomous decision-making under uncertainty. I collaborate with academics and industry organisations to apply my research across various disciplines including healthcare, military defence, sports, economics, and gaming. I lead the Bayesian AI lab and the broader MInDS research group.Publications of specific relevance to the Centre for Multimodal AI
2024
Constantinou AC, Kitson NK and Zanga A (2024). Using GPT-4 to guide causal machine learning. Expert Systems with Applications, Elsevier 12-12-2024
2023
Constantinou A, Kitson NK, Liu Y, Chobtham K, Amirkhizi AH, Nanavati PA, Mbuvha R and Petrungaro B (2023). Open problems in causal structure learning: A case study of COVID-19 in the UK. Expert Systems with Applications, Elsevier vol. 234 01-08-2023
Constantinou AC, Guo Z and Kitson NK (2023). The impact of prior knowledge on causal structure learning. Knowledge and Information Systems, Springer Nature vol. 65 (8), 3385-3434. 08-04-2023
Liu Y and Constantinou A (2023). Improving the imputation of missing data with Markov Blanket discovery. International Conference on Learning Representations (ICLR-2023). 08-02-2023
Kitson NK, Constantinou AC, Guo Z, Liu Y and Chobtham K (2023). A survey of Bayesian Network structure learning. Artificial Intelligence Review, Springer 17-01-2023
2022
Constantinou AC, Liu Y, Kitson NK, Chobtham K and Guo Z (2022). Effective and efficient structure learning with pruning and model averaging strategies. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems, Elsevier vol. 151, 292-321. 13-10-2022
Constantinou AC (2022). Investigating the efficiency of the Asian handicap football betting market with ratings and Bayesian networks. Journal of Sports Analytics vol. 8 (3), 171-193. 15-09-2022
Liu Y and Constantinou AC (2022). Greedy structure learning from data that contain systematic missing values. Machine Learning, Springer 10-08-2022
2021
Constantinou AC, Liu Y, Chobtham K, Guo Z and Kitson NK (2021). Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data. International Journal of Approximate Reasoning, Elsevier vol. abs/2005.09020 25-01-2021
2020
Kitson NK and Constantinou AC (2020). Learning Bayesian networks from demographic and health survey data. Journal of Biomedical Informatics, Elsevier 17-11-2020
Guo Z and Constantinou AC (2020). Approximate learning of high dimensional Bayesian network structures via pruning of Candidate Parent Sets. Entropy, MDPI AG vol. 22 (10) 10-10-2020
Chobtham K and Constantinou AC (2020). Bayesian network structure learning with causal effects in the presence of latent variables. In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM-2020), Aalborg, Denmark 23-09-2020
Constantinou A (2020). The importance of temporal information in Bayesian network structure learning. Expert Systems with Applications, Elsevier vol. 164 17-08-2020
Constantinou AC (2020). Learning Bayesian Networks That Enable Full Propagation of Evidence. IEEE Access vol. 8, 124845-124856. 08-07-2020
2018
CONSTANTINOU AC (2018). Dolores: A model that predicts football match outcomes from all over the world. Machine Learning, Springer Verlag 03-05-2018
CONSTANTINOU AC and FENTON N (2018). Things to know about Bayesian networks. Significance, Royal Statistical Society 16-04-2018
YET B, NEIL M, FENTON N, CONSTANTINOU AC and DEMENTIEV E (2018). An Improved Method for Solving Hybrid Influence Diagrams. International Journal of Approximate Reasoning, Elsevier 01-04-2018
Yet B, Constantinou A, Fenton N and Neil M (2018). Expected Value of Partial Perfect Information in Hybrid Models Using Dynamic Discretization. IEEE Access, Institute of Electrical and Electronics Engineers (IEEE) vol. 6, 7802-7817. 01-01-2018
2017
CONSTANTINOU AC and Fenton N (2017). The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks. PLoS ONE, Public Library of Science (PLoS) vol. 12 (6) 27-06-2017
2016
Coid JW, Ullrich S, Kallis C, Freestone M, Gonzalez R, Bui L, Igoumenou A, Constantinou A, Fenton N, Marsh W, Yang M, DeStavola B, Hu J, Shaw J, Doyle M, Archer-Power L, Davoren M, Osumili B, McCrone P, Barrett K, et al. (2016). Improving risk management for violence in mental health services: a multimethods approach. Programme Grants for Applied Research vol. 4 (16), 1-408. 01-11-2016
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 17-09-2016
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 04-05-2016
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 18-03-2016
Constantinou AC, Fenton N, Marsh W and Radlinski L (2016). From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support. Artificial Intelligence in Medicine, Elsevier vol. 67, 75-93. 16-01-2016
2015
CONSTANTINOU AC, Freestone M, Marsh W and Coid J (2015). Causal inference for violence risk management and decision support in forensic psychiatry. Decision Support Systems vol. 80, 42-55. 08-10-2015
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. Artificial Intelligence in Medicine, Elsevier vol. 66, 41-52. 08-09-2015
Constantinou AC, Freestone M, Marsh W, Fenton NE and Coid J (2015). Risk assessment and risk management of violent re-offending among prisoners. Expert Systems with Applications vol. 42 (21) 28-05-2015
2014
Constantinou AC, Fenton NE and Pollock LJH (2014). Bayesian networks for unbiased assessment of referee bias in Association Football. Psychology of Sport and Exercise, Elsevier vol. 15 (5), 538-547. 01-09-2014
2013
Constantinou A and FENTON NE (2013). Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries. Journal of Quantitative Analysis in Sports vol. 9 (1), 37-50. 01-01-2013
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. 01-01-2013
2012
Constantinou A, FENTON NE and Neil M (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Knowledge Based Systems, Elsevier vol. 36, 322-339. 01-12-2012
Constantinou A and FENTON NE (2012). Solving the problem of inadequate scoring rules for assessing probabilistic football forecasting models. Journal of Quantitative Analysis in Sports vol. 8 (1) 12-03-2012
Grants
Grants of specific relevance to the Centre for Multimodal AIBayesian Artificial Intelligence for Decision Making under UncertaintyAnthony Constantinou
£502,080 EPSRC Engineering and Physical Sciences Research Council (01-06-2018 - 31-05-2021)