Distributed Analytics and Information Science Group
Our research group unlocks the potential of big data and fast data in front line situations, where people and computer systems from multiple agencies need to collaborate.
We are making advances in artificial intelligence, machine learning and network science to improve the capabilities of technology to assist coalitions working together in rapidly-changing situations, such as major disasters, to make people safer.
We bring together colleagues from across the university with specialist expertise in artificial intelligence, machine learning, social computing, signal processing and distributed computing.
Our research spans the themes of:
Able to rapidly adapt in dynamic situations and learn as the operation proceeds exploiting synergies between humans and machine intelligence.
Uncertainty-aware AI, enabling human users to rapidly achieve an appropriate degree of trust in AI systems when making high-stakes decisions.
Distributed Coalition AI able to share data and models with partners while operating under a range of privacy constraints and in DDIL communications environments.
Understanding dynamic audiences
Agent-based modelling of the way in which group and individual psychological behaviours interact, give rise to effects such as prejudice and devotion to a cause, and the emergence of opposed groups.