Skip to main content

Artificial intelligence and machine learning

Our research group investigates artificial intelligence and machine learning, including the nature of intelligence and how to build intelligent systems.

Who we are

Find out more about us and join us at one of our seminars.

Join us

Find out how to join us as a PhD student.

Machine learning

  • Learning on data manifolds: semi-supervised learning, spectral clustering, non-linear data embedding, link prediction
  • Bayesian inference: Large-scale approximate Bayesian inference, latent variable models
  • Learning for computer graphics: Bayesian inference for shape modelling, tracking, sampling, and transfer, machine learning for computational photography, videography, and 3D data analysis
  • Sparse Bayesian models (the “relevance vector machine”) and related novel learning techniques
  • Probabilistic approaches to tree-based pattern recognition
  • Adaptive analysis of multivariate time series
  • Methods for intelligent statistical automation
  • New perspectives on deep neural networks
  • Model-driven data mapping and visualisation techniques
  • Reinforcement learning
View through augmented reality glasses with deep learning analytics to identify people and objects.

Autonomous systems and Agents

Autonomous Systems

  • Robotics
  • Synthetic emotions, and their impact on Human Robot Interaction
  • Intelligent perception, planning and control for autonomous driving
  • Coordination and mapping with UAVs: path planning driven by map and 3D image construction
  • Robot and AI ethics: the ethical design of intelligent systems and their role in society
  • Intelligent assistance for level design, and procedural generation of game content more generally


  • Agent-based modelling/simulation
  • Agent architecture
  • Agents on the web
  • Semantic web technologies
  • Software and systems engineering for multi-agent systems and AI
Nao robot sitting on the floor next to a stack of books.

Natural language processing and Knowledge representation and reasoning

Natural language processing

  • Development of computational models for understanding and generating human language
  • AI and machine learning applications to language tasks
  • Text classification and text mining
  • Applications of NLP: educational technology, intelligent tutoring

Knowledge representation and reasoning

  • Answer Set Programming (ASP) and its applications
  • Norms and institutions as mechanisms for analysis and control
  • Sensor networks
  • Applications (e.g. music composition, planning, legal reasoning)
Students interacting with Nao robot

Research outputs

Take a look at recent papers, articles and conference contributions from our staff and students on Bath research portal.