Dr Vasileios Giagos

School of Mathematics, Statistics and Actuarial Science (SMSAS)
Dr Vasileios Giagos



The two major themes in my research career are stochastic modelling and Bayesian Analysis. In addition to these two major themes, I have an active research interest in the areas of Computational Statistics (MCMC, Particle Filters), Probability (SDEs), Machine Learning and AI with a very wide range of applications (e.g. Epidemiology, Biology, Health, Demographics, and Animal Science). I am very interested in extending the scope of my research with collaborations with the industry and other disciplines.

Research and professional activities

Research interests

Inference for stochastic kinetic dynamics

Stochastic kinetic dynamics provide a modelling framework with a wide range of applications (e.g. Epidemiology, Population Dynamics). The development of inferential tools for the kinetic constants is particularly challenging and involves topics like the Bayesian Prior Specification, the development of efficient simulation algorithms (Markov Chain Monte Carlo, Sequential Monte Carlo, Approximate Bayesian Computation) and stochastic processes (Markov Jump Processes, Linear Noise Approximation, Stochastic Differential Equations).

Key words: Stochastic Processes
Open to supervise

Bayesian Analysis

I have an active research interest in the methodological, computational and applied aspects of Bayesian Analysis. Some examples include Hierarchical models, inference for stochastic processes, Approximate Bayesian Computation, Time Series, Hidden Markov Models, Imputation of Missing Data, and Empirical Bayes. Furthermore, these involve computational aspects like Markov Chain Monte Carlo methods, Particle Filters and Statistical Machine Learning. Finally, areas of applications involve epidemiology, Biology, Health, Animal Science, Demographics, road traffic.

Key words: Bayesian Statistics
Open to supervise

Data Science and Statistical Applications

Together with Prof Hongsheng Dai, Dr Jackie Wong and Dr Yanchun Bao, we are currently working with Croud Inc., supported by a two-year Knowledge Transfer Partnership involving the use of Bayesian Analysis in digital marketing. I am excited to explore research opportunities in data science, leveraging statistical methods to analyze complex datasets from diverse industries and domains, uncovering valuable insights, and proposing innovative solutions to support better-informed decisions.

Key words: Data Science
Open to supervise

Current research

Croud Inc Ltd KTP Grant

I am currently working with Croud Inc Ltd, supported by a two-year KTP grant, together with Vasileios Giagos, Yanchun Bao and an external member Hongsheng Dai at Newcastle University.

Conferences and presentations

Bayesian inference of sampling weights in COVID-19 testing

Invited presentation, The 25th International Conference on Computational Statistics, The 25th International Conference on Computational Statistics, London, 24/8/2023

Teaching and supervision

Current teaching responsibilities

  • Data Visualisation (MA304)

  • Databases and data processing with SQL (MA332)

  • Dissertation with Professional Placement (MA983)

  • Dissertation (MA981)


Publications (1)

Fearnhead, P., Giagos, V. and Sherlock, C., (2012). Inference for reaction networks using the Linear Noise Approximation

Journal articles (5)

Wilcox, C., Giagos, V. and Djahel, S., (2023). A Neighborhood-Similarity-Based Imputation Algorithm for Healthcare Data Sets: A Comparative Study. Electronics. 12 (23), 4809-4809

Jaggi, A., Drake, M., Siddiqui, E., Nazir, J., Giagos, V. and Fatoye, F., (2018). A critical appraisal of the principal guidelines for neurogenic lower urinary tract dysfunction using the AGREE II instrument. Neurourology and Urodynamics. 37 (8), 2945-2950

van den Berg, M., Giagos, V., Lee, C., Brown, WY. and Hinch, GN., (2016). Acceptance of novel food by horses: The influence of food cues and nutrient composition. Applied Animal Behaviour Science. 183, 59-67

van den Berg, M., Giagos, V., Lee, C., Brown, WY., Cawdell-Smith, AJ. and Hinch, GN., (2016). The influence of odour, taste and nutrients on feeding behaviour and food preferences in horses. Applied Animal Behaviour Science. 184, 41-50

Fearnhead, P., Giagos, V. and Sherlock, C., (2014). Inference for reaction networks using the linear noise approximation. Biometrics. 70 (2), 457-466

Conferences (1)

Wilcox, C., Djahel, S. and Giagos, V., (2021). Identifying the Main Causes of Medical Data Incompleteness in the Smart Healthcare Era

Grants and funding


Croud Inc Ltd KTP Application

Innovate UK (formerly Technology Strategy Board)

Croud Inc Ltd KTP Application

Innovate UK (formerly Technology Strategy Board)

+44 (0) 1206 872343


3A.529, Colchester Campus