Dr Miguel Juarez

School of Mathematical and Physical Sciences


+44 114 222 3908

Full contact details

Dr Miguel Juarez
School of Mathematical and Physical Sciences
Hicks Building
Hounsfield Road
S3 7RH

Miguel obtained a PhD in Mathematical Sciences (Statistics) from Universidad de Valencia, Spain in 2004 with a dissertation in Objective Bayesian methods for point estimation and hypothesis testing.
From 2005-2008 he was a research fellow in the Statistics department at University of Warwick dealing with models for panel data that incorporate skewness and heavy tails.
In 2008 he moved to the Warwick Systems Biology Centre as a research fellow in Bayesian analysis of biological data, with a special emphasis in developing models for gene regulatory networks.

In 2010 he joined the School of Mathematics and Statistics as a lecturer in Statistics.

Research interests

Bayesian statistics. Hierarchical modelling for panel and longitudinal data. Image analysis for super-resolution microscopy. In silico augmented clinical trials


Show: Featured publications All publications

Journal articles

All publications

Journal articles


  • (2024) Toward Good Simulation Practice In Viceconti M & Emili L (Ed.) Springer Nature Switzerland RIS download Bibtex download
  • Juarez M, Viceconti M, lowe A, Calvetti D, Somersalo E, Geris L, Horner M & De Cunha Maluf-Burgman M (2024) Theoretical Foundations of Good Simulation Practice In Viceonti M & Emili L (Ed.), Toward Good Simulation Practice Best practices for the use of computational modelling & simulation in the regulatory process of biomedical products (pp. 9-23). Springer RIS download Bibtex download
  • Buck CE & Juárez MA (2020) Modelización bayesiana de radiocarbono para principiantes In Barceló JA & Morell B (Ed.), Cronométricos en Historia y Arqueología (pp. 293-–310). Madrid: Dextra Editorial. RIS download Bibtex download

Conference proceedings papers



  • Curreli C, Pappalardo F, Russo G, Pennisi M, Kiagias D, Juarez M, Viceconti M & . (2021) Verification of an agent-based disease model of human mycobacterium tuberculosis infection, arXiv. RIS download Bibtex download
  • Pennisi M, Juarez MA, Russo G, Viceconti M & Pappalardo F (2019) Generation of digital patients for the simulation of tuberculosis with UISS-TB, arXiv. RIS download Bibtex download
  • Russo G, Pappalardo F, Juarez MA, Pennisi M, Cardona PJ, Coler R, Fichera E & Viceconti M (2019) Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulator, arXiv. RIS download Bibtex download
  • Viceconti M, Juárez MA, Curreli C, Pennisi M, Russo G & Pappalardo F (2019) POSITION PAPER: Credibility of In Silico Trial Technologies: A Theoretical Framing, arXiv. RIS download Bibtex download
Research group


Mathematical Biology

Teaching activities
MAS360 Practical and Applied Statistics
MAS464 Bayesian Statistics