Research Directions
🩺 AI for Science: Sequential Decision Making for Infectious Disease
Our research in this area focuses on adaptive AI systems that can learn and act in complex scientific and epidemiological settings.
Current directions include:
- 🌍 Spatiotemporal forecasting and resource allocation for healthcare and epidemic response
- 📈 Nowcasting and forecasting of epidemic trajectories using dynamic data
- 🔄 Non-stationary decision making for evolving spatial–temporal signals
- 🧩 Sequential disease surveillance and control through reinforcement learning
🤖 Foundation Models for Epidemiology and Adaptive Inference
This direction focuses on developing and applying foundation models for epidemiological forecasting and decision support.
Research emphasises how large, pretrained models can be adaptively fine-tuned or updated at test time to improve robustness and generalization under data drift and uncertainty.
- 🧠 Epidemiology foundation models for spatial–temporal health forecasting and intervention planning
- ⚙️ Test-time adaptive inference and fine-tuning for rapidly evolving data environments
Reaching Out
If you are interested in the research directions above, please email me (mengyan.zhang@bristol.ac.uk) with [PhD Application + Your name] in the subject line. You will need:
- A CV;
- A Personal Statement, which is a one- to two-page document introducing yourself and outlining your motivation for PhD research;
- A transcript of any qualifying degrees (completed and/or underway);
- A research proposal (optional, but preferable);
- Any additional materials to support your application, e.g. research outputs, thesis, coding repository, etc.
Due to the volume of enquiries, only shortlisted candidates may receive a response.
PhD Opportunities
Fully funded PhD opportunities are available:
- University PhD program
- China Scholarship Council-University of Bristol PhD Scholarship (CSC)
- Centres for Doctoral Training (CDTs)
I am also willing to be a secondary supervisor for PhD students in related areas.