Prof Jeremy Oakley


Position: Professor
Home page: http://www.jeremy-oakley.staff.shef.ac.uk/
Email:
Telephone: (0114) 2223853
Office: I16 Hicks building
Photo of Jeremy Oakley

Personal assistant:

Name:
Email:

Teaching:

MAS5052 Basic Statistics Information  
MAS61004 The Statistician's Toolkit Information  
MAS61006 Bayesian Statistics and Computational Methods Information  


Research:


Interests: Bayesian statistics; eliciting probability distributions; health economics; uncertainty quantification for complex computer models
Research group: Statistics
Publications: MathSciNet

Grants

Past grants, as Principal Investigator
Gaussian Process Emulators for Numerical Models
INO
Simulation Tools for Automated and Robust Manufacturing EPSRC
Match+
Past grants, as Coinvestigator
Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models EPSRC
Development of a fully Bayesian framework for the identification and estimation of subgroup effects in Randomised Controlled Trials
MRC
Calibration and analysis of complex models: methodological development and application to explore the impact of HAART in Africa
MRC
Managing Uncertainty in Complex Models 2 (MUCM2) EPSRC
Managing Uncertainty in Complex Models EPSRC
Coupled models: Expert judgement, emulators and model uncertainty EPSRC
Simplicity, complexity and modelling EPSRC
BAMRA: Bayesian approaches in microbial risk assessment (Working group) NERC
Mathematics for data modelling EPSRC
The probability of rapid climate change NERC
The probability of rapid climate change NERC

Roles:

Head of School

Biography:

Professor Oakley obtained his BSc (1996) in Mathematics and Statistics from the University of Nottingham, and his PhD (2000) in Statistics from the University of Sheffield. He has worked as a post- doctoral research associate in both the Department of Computer Science and Department of Probability and Statistics, University of Sheffield, before starting a lectureship in Probability and Statistics in 2002. He has various research interests in Bayesian statistics including uncertainty quantification for computer models, prior elicitation and Bayesian methods in health economics.