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AIRC aims to develop cutting-edge AI theories, algorithms and tools, and to create state of the art AI solutions for practical problems through engagement with stakeholders and users, and alignment with University, local, national and European initiatives.

AIRC operates across a number of key research areas.

Foundations of Artificial Intelligence

  • Mathematical modelling: opinion dynamics, ecological networks, pandemic modelling
  • Mathematical optimisation: multi-objective optimisation and Bayesian optimisation
  • Cryptography and pure algebra
  • Enumerative combinatorics

Machine Learning

  • Classification, clustering, reinforcement learning
  • Detection learning
  • Interpretable machine learning
  • Big data analytics
  • Feature selection/extraction

Knowledge Engineering

  • Knowledge representation and ontology
  • Reasoning: probability/uncertainty reasoning, explanation and abductive reasoning
  • Logics: classical/multi-valued logics, theorem proving, formal verification and Boolean satisfiability problem
  • Decision making and risk assessment
  • Data and knowledge modelling

Data Analytics and Systems

  • Bioinformatics: multiplex network, protein–protein interaction
  • Geo-informatics: satellite and ground based data analytics for earth anomaly detection
  • Digital intervention and chatbots
  • Autonomic computing and swarm systems
  • Synthetic data generation
  • Text analytics: summarisation, matching, sentiment analysis
  • Video/Image analytics: face recognition/verification, event recognition, medical image analysis
  • Information retrieval and video search
  • Biometrics: face recognition, palmprint recognition, biomarker recognition
  • Detection analytics: event detection, change detection, intrusion detection, anomaly detection