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Research

Computer Science students and building

Research Objectives

  • To engage in inter-/multi-disciplinary research to improve quality of life, health, national security, education and social cohesion;
  • To develop new computing science techniques and seek methods of application and commercialisation;
  • To provide leading advice and knowledge transfer to government and industry, and promote jobs and growth through technical innovation.

Focus, Impact, Strengths

AI & ML Systems

Scalable and efficient ML; Generative AI and natural language processing; Graph and spatio-temporal learning; Ethical and trustworthy AI; Vision, embodied and pervasive intelligence; social and health informatics

Biomedical Data Analytics

Multimodal AI for biomedical applications; Computational pathology; Computational neuroscience; Systems and synthetic biology

Foundations of AI & ML

Learning Efficiency & Complexity; Robustness, Fairness, and Privacy; Multiagent Systems, RL & Game Theory; Generative AI & Alignment, Causality & Causal Inference; Quantum Computing and Learning Theory; Stochastic Processes & Diffusions; Physics-informed ML

Systems and Security

High-performance, secure, dependable and scalable systems; cryptographic protocols; AI and cybersecurity; large-scale scientific codes on massively parallel and high-performance architectures; parallel and distributed computing techniques

Theory and Foundations

Topics of theoretical Computer Science; Design and analysis of algorithms; Complexity theory; Logic; Automation; Formal verification

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