Dr Jessica Bridgen
Lecturer in Mathematical AIResearch Overview
My research focuses on modelling complex systems. These are often stochastic dynamical systems that are only partially observed, such as infection transmission in hospitals, human mobility, or disease spread through livestock movement networks. I am particularly interested in scalable Bayesian inference for calibrating these models to data in real time, with the aim of providing decision-time evidence. My main application is currently hospital infection control, where models can help identify the drivers of transmission and inform where control measures should be targeted.
PhD Supervision Interests
I am interested in supervising projects on dynamical modelling, processes on networks, and Bayesian inference, with applications in infectious disease epidemiology and ecology.
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Evaluation of Testing Effectiveness in Schools during the SARS COVID-19 Pandemic
01/01/2024 → 31/12/2024
Research
20 schools from across the North West, North East and Yorkshire
School Engagement
20 schools from across the North West, North East and Yorkshire
School Engagement
A Bayesian approach to identifying routes of infectious disease transmission in clinical settings
Invited talk
Grant review
Review of Award Applications
IMA Mathematical Medicine and Biology (Journal)
Publication peer-review
BMC Public Health (Journal)
Publication peer-review
Real-time modelling of nosocomial transmission
Participation in workshop, seminar, course
ISVEE
Participation in conference -Mixed Audience
Introduction to JAX
Invited talk
Gem: Probabilistic programming for epidemic models
Invited talk
Epidemics (Journal)
Publication peer-review
PeerJ (Journal)
Publication peer-review
SPI-M-O award for Modelling and Data Support during the COVID-19 pandemic
Prize (including medals and awards)
STOR-i Centre for Doctoral Training
MARS: Mathematics for AI in Real-world Systems
- Bayesian and Computational Statistics
- Biostatistics
- MARS: Mathematics for AI in Real-world Systems