Rob Deardon

Rob Deardon



Faculty of Veterinary Medicine

Adjuct Professor

Community Health Sciences

Contact information


Educational Background

PhD Applied Statistics, University of Reading, 2001

MSc Medical Statistics, University of Southampton, 1997

BSc (Hons) Pure Mathematics & Mathematical Statistics, University of Exeter, 1996


Dr Deardon is a Professor of Biostatistics, who has been working jointly in the Faculty of Veterinary Medicine (Dept. of Production Animal Health) and the Department of Mathematics & Statistics at The University of Calgary since September 2014.

He obtained his PhD at the University of Reading in the UK in 2001. After a brief interlude at the University of Warwick, he took up a postdoctoral position at the University of Cambridge working with Professors Steve Brooks and James Wood on infectious disease modelling -- primarily working on modelling the UK 2001 foot-and-mouth disease epidemic.

Following this he worked as an Assistant, and then Associate, Professor in the Department of Mathematics & Statistics at the University of Guelph, from 2006 to 2014.


Areas of Research

Ecosystem Health
Immunology and Infectious Disease
Public Health

Dr Deardon has research interests in the areas of Bayesian & computational statistics, infectious disease epidemiology (transmission modelling and disease surveillance methods), spatial and spatio-temporal modelling, experimental design, statistical learning, ecological modelling, clustering and classification, and statistical modelling in general.

In infectious disease modeling, an area which has provided the mainstay of his research over the past few years, he has worked on various diseases of animals and humans, including foot and mouth disease, influenza, Ebola, porcine reproductive and respiratory syndrome (PRRS), as well as diseases of crops such as tomato spotted wilt virus (TSWV).

From a statistical perspective, Dr. Deardon has interests in Monte Carlo methods such as Markov chain Monte Carlo (MCMC), approximate Bayesian computation (ABC), emulation and classification-based inference. He has also worked in high dimensional problems in areas such as bioinformatics, image analysis, random forest-based classification, and variable selection techniques such as the lasso.

He currently has a research group consisting of around 10 PhD and MSc students. Any prospective graduate students interested in working with Dr. Deardon should contact him via e-mail. Such students could enroll in various programs (e.g. Statistics, Veterinary Medical Sciences, Community Health, etc.) at the University of Calgary.


Course number Course title Semester
STAT 601.29 Topics in Probability and Statistics (Infectious Disease Modelling) Winter