The Bayesian Artificial Intelligence research lab was established in late 2018, as part of the EPSRC Fellowship project “Bayesian Artificial Intelligence for Decision Making under Uncertainty”. The lab’s research focuses on Bayesian Networks (BNs) and the different approaches that can be used to generate them. These include a) machine learning, statistical, and probabilistic methods to discover the graphical structure and estimate the parameters of the variables, and the magnitude of relationships between variables, b) data engineering and information fusion methods to combine data with rule-based, temporal, and knowledge-based information, and c) methods from game-theory and decision-theory for optimal decision making.
Broadly, the lab’s research activities include:
- Artificial Intelligence
- Bayesian Inference
- Causal Discovery
- Data Engineering
- Game Theory
- Knowledge-Based Systems
- Machine Learning
- Risk Management
- Statistics and Probability Theory
- Uncertainty Quantification
We apply our research to a wide range of fields including finance, sports, medicine, forensics, and gaming.
The lab has a close collaboration with the Risk Information Management research group, the Alan Turing Institute, and Agena Ltd, the UK company that develops the Bayesian risk and decision analysis software called AgenaRisk.