Staff profile

Current research

My main research interests are in Bayesian approaches to modelling and uncertainty quantification. I am mostly interested in the development and implementation of models and the design of emulators (statistical representations) for large complex systems such as health, climate, and population dynamics. My current research is focused on multi-model uncertainty looking at frameworks for assimilating multiple models and experts’ beliefs, the aim of these frameworks is to unify multiple uncertainty specifications and provide an accessible decision support mechanism. This approach is essential when studying systems such as health where fast and reliable tools are necessary to aid decision making or such as climate where different modeling approaches are used by experts in different areas to inform policy makers. My current collaborations involve the development of Bayesian methods and their application to a number of areas including health, engineering, societal dynamics, climate, seismology, and banking. Most of these partnerships are generating substantial outputs with current and eminent impact in the local industry and society.

• Bayesian Statistics
• Parametric Inference
• Information Theory
• Stochastic Processes

Authored book

• Tipping Points: Modelling Social Problems and Health
  
  Bissell, J., Caiado, C., Curtis, S., Goldstein, M., & Straughan, B. (2015). Tipping Points: Modelling Social Problems and Health. Wiley. https://doi.org/10.1002/9781118992005

Chapter in book

• Digital Banking—Building Atom bank’s Digital Twin
  
  Caiado, C. C., Huntley, N., & Twiddy, E. (2025). Digital Banking—Building Atom bank’s Digital Twin. In P. J. Aston (Ed.), More UK Success Stories in Industrial Mathematics (pp. 221-227). https://doi.org/10.1007/978-3-031-48683-8_28
• Stochastic Modelling for Compartmental Systems Applied to Social Problems
  
  Caiado, C. (2015). Stochastic Modelling for Compartmental Systems Applied to Social Problems. In J. Bissell, C. Caiado, S. Curtis, M. Goldstein, & B. Straughan (Eds.), Tipping Points: Modelling Social Problems an Health. Wiley. https://doi.org/10.1002/9781118992005.ch2
• Cardiac Surgery Performance Monitoring
  
  Hickey, G., Grant, S., Caiado, C., Buchan, I., & Bridgewater, B. (2015). Cardiac Surgery Performance Monitoring. In J. Bissell, C. Caiado, S. Curtis, M. Goldstein, & B. Straughan (Eds.), Tipping Points: Modelling Social Problems an Health. Wiley. https://doi.org/10.1002/9781118992005.ch4
• Heart Online Uncertainty and Stability Estimation
  
  Caiado, C., Hickey, G., Grant, S., Goldstein, M., Markarian, G., McCollum, C., & Bridgewater, B. (2015). Heart Online Uncertainty and Stability Estimation. In J. Bissell, C. Caiado, S. Curtis, M. Goldstein, & B. Straughan (Eds.), Tipping Points: Modelling Social Problems an Health. Wiley. https://doi.org/10.1002/9781118992005.ch5
• Complexity in Spatial Dynamics: The Emergence of Homogeneity/Heterogeneity in Culture in Cities
  
  Bentley, R., Caiado, C., & Ormerod, P. (n.d.). Complexity in Spatial Dynamics: The Emergence of Homogeneity/Heterogeneity in Culture in Cities. In J. Bissell, C. Caiado, S. Curtis, M. Goldstein, & B. Straughan (Eds.), Tipping Points: Modelling Social Problems an Health [Contracted by publisher]. Wiley.

Conference Paper

• Patterns Of Social Care Use Within The Older Population: What Can We Learn From Routinely Collected Data?
  
  Brotherhood, K., Hanratty, B., Spiers, G., Caiado, C., & Newton, J. (2023). Patterns Of Social Care Use Within The Older Population: What Can We Learn From Routinely Collected Data?. Innovation in Aging [Conference abstract], 7(Supplement_1), 707. https://doi.org/10.1093/geroni/igad104.2294
• Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques
  
  Formentin, H. N., Vernon, I., Goldstein, M., Caiado, C., Avansi, G., & Schiozer, D. (2020, September). Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques. Presented at ECMOR XVII. https://doi.org/10.3997/2214-4609.202035095
• Improving and benchmarking of algorithms for decision making with lower previsions
  
  Nakharutai, N., Troffaes, M. C., & Caiado, C. (2019, July 3 – 2019, July 6). Improving and benchmarking of algorithms for decision making with lower previsions [Conference paper]. Presented at ISIPTA 2019, Ghent, Belgium.
• Efficient algorithms for checking avoiding sure loss
  
  Nakharutai, N., Troffaes, M. C., & Caiado, C. C. (2017). Efficient algorithms for checking avoiding sure loss. In A. Antonucci, G. Corani, I. Couso, & S. Destercke (Eds.), Proceedings of the Tenth International Symposium on Imprecise Probability : Theories and Applications, 10-14 July 2017, Lugano (Switzerland). (pp. 241-252). PMLR.
• A two parameter skew distribution function
  
  Rathie, P., Swamee, P., & Caiado, C. (2008). A two parameter skew distribution function. In Proceedings of the second World Aqua Congress.
• New intensity functions in hydraulic repairable systems
  
  Rathie, P., Caiado, C., & Swamee, P. (2008). New intensity functions in hydraulic repairable systems. In Proceedings of National Conference on Hydraulics and Water Resources.
• Repairable Systems in Reliability Theory
  
  Rathie, P., & Caiado, C. (2007). Repairable Systems in Reliability Theory. In Proceedings of the VI International Conference on Operational Research for Development.
• Polynomial Coefficients and Distribution of the Sum of Discrete Uniform Variables
  
  Caiado, C., & Rathie, P. (2007). Polynomial Coefficients and Distribution of the Sum of Discrete Uniform Variables (M. A. M., P. M. A., J. K. K., & J. Joy, Eds.). Society for Special Functions & their Applications.

Journal Article

• Understanding health service utilisation patterns for care home residents during the COVID-19 pandemic using routinely collected healthcare data
  
  Garner, A., Preston, N., Caiado, C., Stubington, E., Hanratty, B., Limb, J., Mason, S., & Knight, J. (2024). Understanding health service utilisation patterns for care home residents during the COVID-19 pandemic using routinely collected healthcare data. BMC Geriatrics, 24(1), Article 449. https://doi.org/10.1186/s12877-024-05062-6
• Variations in older people's emergency care use by social care setting: a systematic review of international evidence.
  
  Brotherhood, K., Searle, B., Spiers, G. F., Caiado, C., & Hanratty, B. (2024). Variations in older people’s emergency care use by social care setting: a systematic review of international evidence. British Medical Bulletin, 149(1), 32-44. https://doi.org/10.1093/bmb/ldad033
• The impact of digital technology in care homes on unplanned secondary care usage and associated costs.
  
  Garner, A., Lewis, J., Dixon, S., Preston, N., Caiado, C. C. S., Hanratty, B., Jones, M., Knight, J., & Mason, S. M. (2024). The impact of digital technology in care homes on unplanned secondary care usage and associated costs. Age and Ageing, 53(2), Article afae004. https://doi.org/10.1093/ageing/afae004
• Machine learning for determining lateral flow device results for testing of SARS-CoV-2 infection in asymptomatic populations
  
  Beggs, A. D., Caiado, C. C., Branigan, M., Lewis-Borman, P., Patel, N., Fowler, T., Dijkstra, A., Chudzik, P., Yousefi, P., Javer, A., Van Meurs, B., Tarassenko, L., Irving, B., Whalley, C., Lal, N., Robbins, H., Leung, E., Lee, L., & Banathy, R. (2022). Machine learning for determining lateral flow device results for testing of SARS-CoV-2 infection in asymptomatic populations. Cell Reports Medicine, 3(10), Article 100784. https://doi.org/10.1016/j.xcrm.2022.100784
• Durham University students’ experiences of asymptomatic COVID-19 testing: a qualitative study
  
  Jones, L. F., Batteux, E., Bonfield, S., Bhogal, J. K., Taylor, J., Caiado, C., Ramagge, J., & Weston, D. (2021). Durham University students’ experiences of asymptomatic COVID-19 testing: a qualitative study. BMJ Open, 11(12). https://doi.org/10.1136/bmjopen-2021-055644
• Improving and benchmarking of algorithms for Γ-maximin, Γ-maximax and interval dominance
  
  Nakharutai, N., Troffaes, M. C., & Caiado, C. C. (2021). Improving and benchmarking of algorithms for Γ-maximin, Γ-maximax and interval dominance. International Journal of Approximate Reasoning, 133, 95-115. https://doi.org/10.1016/j.ijar.2021.03.005
• Justified Stories with Agent-Based Modelling for Local COVID-19 Planning
  
  Badham, J., Barbrook-Johnson, P., Caiado, C., & Castellani, B. (2021). Justified Stories with Agent-Based Modelling for Local COVID-19 Planning. Journal of Artificial Societies and Social Simulation, 24(1), Article 8. https://doi.org/10.18564/jasss.4532
• Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty Analysis
  
  Ferreira, C., Vernon, I., Caiado, C., Formentin, H., Avansi, G., Goldstein, M., & Schiozer, D. (2020). Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty Analysis. SPE Journal, 25(4), 2119-2142. https://doi.org/10.4043/29801-ms
• A Novel Patient-Specific Model for Predicting Severe Oliguria; Development and Comparison With Kidney Disease: Improving Global Outcomes Acute Kidney Injury Classification
  
  Howitt, S. H., Oakley, J., Caiado, C., Goldstein, M., Malagon, I., McCollum, C., & Grant, S. W. (2020). A Novel Patient-Specific Model for Predicting Severe Oliguria; Development and Comparison With Kidney Disease: Improving Global Outcomes Acute Kidney Injury Classification. Critical Care Medicine, 48(1), e18-e25. https://doi.org/10.1097/ccm.0000000000004074
• Improving and benchmarking of algorithms for decision making with lower previsions
  
  Nakharutai, N., Troffaes, M. C., & Caiado, C. (2019). Improving and benchmarking of algorithms for decision making with lower previsions. International Journal of Approximate Reasoning, 113, 91-105. https://doi.org/10.1016/j.ijar.2019.06.008
• Evaluating betting odds and free coupons using desirability
  
  Nakharutai, N., Caiado, C. C., & Troffaes, M. C. (2019). Evaluating betting odds and free coupons using desirability. International Journal of Approximate Reasoning, 106, 128-145. https://doi.org/10.1016/j.ijar.2019.01.002
• Monte Carlo sampling for error propagation in linear regression and applications in isochron geochronology
  
  Li, Y., Zhang, S., Hobbs, R., Caiado, C., Sproson, A., Selby, D., & Rooney, A. (2019). Monte Carlo sampling for error propagation in linear regression and applications in isochron geochronology. Science Bulletin, 64(3), 189-197. https://doi.org/10.1016/j.scib.2018.12.019
• Gaining more understanding about reservoir behavior through assimilation of breakthrough time and productivity deviation in the history matching process
  
  Formentin, H. N., Almeida, F. la R., Avansi, G. D., Maschio, C., Schiozer, D. J., Caiado, C., Vernon, I., & Goldstein, M. (2019). Gaining more understanding about reservoir behavior through assimilation of breakthrough time and productivity deviation in the history matching process. Journal of Petroleum Science and Engineering, 173, 1080-1096. https://doi.org/10.1016/j.petrol.2018.10.045
• Improved linear programming methods for checking avoiding sure loss
  
  Nakharutai, N., Troffaes, M. C., & Caiado, C. C. (2018). Improved linear programming methods for checking avoiding sure loss. International Journal of Approximate Reasoning, 101, 293-310. https://doi.org/10.1016/j.ijar.2018.07.013
• The KDIGO acute kidney injury guidelines for cardiac surgery patients in critical care: a validation study
  
  Howitt, S. H., Grant, S. W., Caiado, C., Carlson, E., Kwon, D., Dimarakis, I., Malagon, I., & McCollum, C. (2018). The KDIGO acute kidney injury guidelines for cardiac surgery patients in critical care: a validation study. BMC Nephrology, 19(1), Article 149. https://doi.org/10.1186/s12882-018-0946-x
• Emulation of reservoir production forecast considering variation in petrophysical properties
  
  Moreno, R., Avansi, G., Schiozer, D., Vernon, I., Goldstein, M., & Caiado, C. (2018). Emulation of reservoir production forecast considering variation in petrophysical properties. Journal of Petroleum Science and Engineering, 165, 711-725. https://doi.org/10.1016/j.petrol.2018.02.056
• Validation of Three Postoperative Risk Prediction Models for Intensive Care Unit Mortality after Cardiac Surgery
  
  Grant, S., Venkateswaran, R., Malagon, I., Goldstein, M., McCollum, C., Caiado, C., & Howitt, S. (2018). Validation of Three Postoperative Risk Prediction Models for Intensive Care Unit Mortality after Cardiac Surgery. Thoracic and Cardiovascular Surgeon, 66(8), 651-660. https://doi.org/10.1055/s-0037-1608897
• Market Structure with Interacting Consumers
  
  Ormerod, P., & Caiado, C. C. (2017). Market Structure with Interacting Consumers. Review of Behavioral Economics., 4(1), 33-49. https://doi.org/10.1561/105.00000057
• Fitness landscapes among many options under social influence
  
  Caiado, C., Brock, W., Bentley, R., & O’Brien, M. (2016). Fitness landscapes among many options under social influence. Journal of Theoretical Biology, 405, Article S0022-5193(16)00014-X. https://doi.org/10.1016/j.jtbi.2015.12.013
• Markov Chain Monte Carlo inversion of temperature and salinity structure of an internal solitary wave packet from marine seismic data
  
  Tang, Q., Hobbs, R., Zheng, C., Biescas, B., & Caiado, C. (2016). Markov Chain Monte Carlo inversion of temperature and salinity structure of an internal solitary wave packet from marine seismic data. Journal of Geophysical Research: Oceans, 121(6), 3692-3709. https://doi.org/10.1002/2016jc011810
• Evaluating reproductive decisions as discrete choices under social influence
  
  Bentley, R., Brock, W., Caiado, C., & O’Brien, M. (2016). Evaluating reproductive decisions as discrete choices under social influence. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1692), Article 20150154. https://doi.org/10.1098/rstb.2015.0154
• Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points
  
  Caiado, C., & Goldstein, M. (2015). Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points. Communications in Nonlinear Science and Numerical Simulation, 26(1-3), 123-136. https://doi.org/10.1016/j.cnsns.2015.02.006
• Estimating a Path through a Map of Decision Making
  
  Brock, W., Bentley, R., O’Brien, M., & Caiado, C. (2014). Estimating a Path through a Map of Decision Making. PLoS ONE, 9(11), Article e111022. https://doi.org/10.1371/journal.pone.0111022
• Social tipping points and Earth systems dynamics
  
  Bentley, R. A., Maddison, E. J., Ranner, P. H., Bissell, J. J., Caiado, C. C. C. S., Bhatanacharoen, P., Clark, T., Botha, M., Akinbami, F., Hollow, M., Michie, R., Huntley, B., Curtis, S., & Garnett, P. (2014). Social tipping points and Earth systems dynamics. Frontiers in Environmental Science, 2, Article 35. https://doi.org/10.3389/fenvs.2014.00035
• Effects of memory on spatial heterogeneity in neutrally transmitted culture
  
  Bentley, R., Caiado, C., & Ormerod, P. (2014). Effects of memory on spatial heterogeneity in neutrally transmitted culture. Evolution and Human Behavior, 35(4), 257-263. https://doi.org/10.1016/j.evolhumbehav.2014.02.001
• Dynamic prediction modeling approaches for cardiac surgery
  
  Hickey, G., Grant, S., Caiado, C., Kendall, S., Dunning, J., Poullis, M., Buchan, I., & Bridgewater, B. (2013). Dynamic prediction modeling approaches for cardiac surgery. Circulation: Cardiovascular Quality and Outcomes, 6(6), 649-658. https://doi.org/10.1161/circoutcomes.111.000012
• Bayesian Strategies to Assess Uncertainty in Velocity Models
  
  Caiado, C. C., Goldstein, M., & Hobbs, R. W. (2012). Bayesian Strategies to Assess Uncertainty in Velocity Models. Bayesian Analysis, 7(1), 211-234. https://doi.org/10.1214/12-ba707

Report

• Bayesian Inference in Non-Homogeneous Poisson Processes.
  
  Caiado, C., & Da-Silva, C. (2006). Bayesian Inference in Non-Homogeneous Poisson Processes.
• Entropias e Índices Caudais
  
  Caiado, C., & Rathie, P. (2005). Entropias e Índices Caudais.
• Multinomial triangle coefficient and distribution of the sum of discrete uniform variates
  
  Caiado, C., & Rathie, P. (2005). Multinomial triangle coefficient and distribution of the sum of discrete uniform variates.
• Birthday Problem e Generalizações (The Birthday Problem and Generalizations)
  
  Caiado, C., & Rathie, P. (2004). Birthday Problem e Generalizações (The Birthday Problem and Generalizations).