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Camila Caiado, BSc in Statistics, PhD in Mathematical Sciences Durham University

Associate Professor, Statistics in the Department of Mathematical Sciences
Telephone: +44 (0) 191 33 42561
Room number: CM321

Contact Camila Caiado (email at

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.

Research Groups

Department of Mathematical Sciences

Research Interests

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


Authored book

Chapter in book

Conference Paper

  • Nakharutai, Nawapon, Troffaes, Matthias C. M. & Caiado, Camila C. C. S. (2017), Efficient algorithms for checking avoiding sure loss, in Antonucci, Alessandro, Corani, Giorgio, Couso, Inés & Destercke, Sébastien eds, Proceedings of Machine Learning Research 62: The Tenth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA ’17). Lugano, Switzerland, PMLR, 241-252.
  • Rathie, P.N., Swamee, P.K. & Caiado, C.C.S. (2008), A two parameter skew distribution function, Proceedings of the second World Aqua Congress World Aqua Congress (WAC2008). New Delhi, India.
  • Rathie, P.N., Caiado, C.C.S. & Swamee, P.K. (2008), New intensity functions in hydraulic repairable systems, Proceedings of National Conference on Hydraulics and Water Resources National Conference on Hydraulics and Water Resources (Hydro 2008). Jaipur, India.
  • Caiado, C.C.S. & Rathie, P.N. (2007), Polynomial Coefficients and Distribution of the Sum of Discrete Uniform Variables, in Mathai, A. M., Pathan, M. A. Jose, K. K. & Jacob, Joy eds, Eighth Annual Conference of the Society of Special Functions and their Applications. Pala, India, Society for Special Functions & their Applications, Pala.
  • Rathie, P.N. & Caiado, C.C.S. (2007), Repairable Systems in Reliability Theory, Proceedings of the VI International Conference on Operational Research for Development International Conference on Operational Research for Development (ICORD VI). Fortaleza, Brazil, Fortaleza.

Journal Article


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


Selected Grants

  • 2017: Bayesian Optimisation of X-Ray Materials Characterisation Phase VII - Further Applications to Medical Imaging (£11154.00 from )
  • 2016: Atom Bank (£279172.00 from Atom Bank)
  • 2016: Bayesian Optimisation of Xray Materials Characterisation phase V1 Applications to Health (£20000.00 from IBEX Innovations)
  • 2016: Connected Health Cities (£147406.76 from Department of Health)
  • 2015: Bayesian optimisation of X-ray Materials Characterisation - phase V (£10000.00 from Ibex Innovations Ltd)
  • 2015: Predictor Feasibility Study (£23810.00 from Innovate UK)
  • 2013: Bayesian optimisation of X-ray materials characterisation phase III (£21526.00 from Ibex Innovations Ltd)