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What We Do

Research at NGAIRC

Six interconnected domains driving the next generation of AI innovation, supported by open publication, international collaboration and a commitment to responsible practice.

Research Domains

Our Research Fields

Six interconnected domains driving the next generation of AI innovation.

Secure, Trustworthy & Responsible AI

Advancing secure, resilient, and ethically governed AI for a trustworthy digital future.

Scalable & Distributed Intelligent Systems

Engineering scalable and distributed intelligence for real-world deployment.

AI for Health, Special Needs & Social Impact

Translating AI innovation into equitable healthcare and societal impact.

Sustainable & Climate-Resilient Intelligent Systems

Driving sustainable innovation through climate-resilient intelligent technologies.

Benchmark Datasets & Open Research Infrastructure

Building trusted data foundations for reproducible and transparent AI research.

Diversity, Inclusion & Human-Centred AI

Embedding human values, diversity, and equity at the core of intelligent innovation.

Our Mission

Advancing AI for the Benefit of All

NGAIRC is a multidisciplinary research centre committed to producing world-class AI research that is responsible, inclusive, and impactful. We bridge the gap between theoretical innovation and real-world application across academia and industry.

  • International collaboration with leading universities and research institutes
  • Open-access publications in top-tier journals and conferences
  • PhD, postdoctoral, and industry training programmes
  • Ethical AI frameworks and policy engagement
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Research Domains
Global
Reach across academia & industry worldwide
Latest Output

Recent Publications

Selected recent work from our researchers.

Journal
Deep Learning Approaches for Intrusion Detection in Cyber-Physical Systems: A Comprehensive Survey
Islam MM, Chowdhury A, et al.
IEEE Transactions on Neural Networks, 2024
Conference
Federated Learning with Differential Privacy for Healthcare Data: Balancing Utility and Privacy
Kamruzzaman J, Islam MM, et al.
AAAI 2024
Journal
Explainable AI for Clinical Decision Support: Bridging the Gap Between Performance and Interpretability
Chowdhury A, et al.
Nature Machine Intelligence, 2024
Conference
Climate-Aware Resource Allocation in Edge Computing Using Reinforcement Learning
Islam MM, et al.
NeurIPS 2024
Workshop
Towards Inclusive AI: Bias Detection and Mitigation in Large Language Models
Kamruzzaman J, Chowdhury A, et al.
FAccT 2024
Journal
A Benchmark Dataset for Multi-Modal Human Activity Recognition Under Real-World Constraints
Islam MM, et al.
Scientific Data, Nature 2024
Meet Our Researchers