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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01/01/2024 → 31/12/2024
Research
School Engagement
School Engagement
Invited talk
Publication peer-review
Publication peer-review
Review of Award Applications
Participation in workshop, seminar, course
Invited talk
Invited talk
Participation in conference -Mixed Audience
Publication peer-review
Publication peer-review
Prize (including medals and awards)
STOR-i Centre for Doctoral Training
MARS: Mathematics for AI in Real-world Systems
MARS: Mathematics for AI in Real-world Systems
MARS: Mathematics for AI in Real-world Systems
- Bayesian and Computational Statistics
- Biostatistics
- MARS: Mathematics for AI in Real-world Systems