Australian Artificial Intelligence Institute
University of Technology Sydney
Advancing the theoretical foundations, innovative technologies, and real-world applications of artificial intelligence.
🌐 Official Website · 🔬 Our Research · 👥 Research Team
About AAII
The Australian Artificial Intelligence Institute (AAII) at the University of Technology Sydney (UTS) is Australia’s largest research hub dedicated to artificial intelligence. Led by Distinguished Professor Jie Lu AO, AAII is internationally recognised for excellence in AI research, collaboration, education, and technology translation.
Established at UTS in 2017 and elevated to institute status in 2020, AAII brings together 35 academic staff, 10 postdoctoral fellows, and more than 200 PhD students across eight key research laboratories. Its research spans fundamental AI, technology transfer, and real-world applications with significant scientific, social, and economic impact.
Research Areas
Our research covers a broad spectrum of artificial intelligence, including:
- Machine learning, deep learning, and representation learning
- Large language models and foundation models
- Computational intelligence and autonomous learning
- Computer vision and pattern recognition
- Reinforcement learning and transfer learning
- Responsible, explainable, secure, and privacy-preserving AI
- Concept drift and learning from evolving data
- Graph learning, network analytics, and data science
- Brain–computer interfaces and neuromorphic computing
- Biomedical AI, bioinformatics, and predictive genomics
- Decision intelligence and human–machine collaboration
AAII translates foundational research into applications across healthcare, finance, transportation, defence, education, telecommunications, agriculture, and other critical sectors.
Open Research on Hugging Face
Our research on Hugging Face is organised into thematic collections, bringing together related papers, datasets, models, and open-source resources.
🔄 Concept Drift — Robust and adaptive learning under evolving distributions, spanning multimodal pre-training, non-stationary custom-tuning, heterogeneous multi-stream learning, and reasoning alignment.
🔁 Transfer Learning — Methods for transferring knowledge across domains, tasks, and distributions to improve data efficiency, adaptation, and generalisation in limited-data settings.
🎯 Recommender Systems — Intelligent and adaptive recommendation methods that model user preferences, heterogeneous information, and evolving interactions to support personalised decision-making.
Please refer to the corresponding repository card for licensing conditions, citations, intended uses, and limitations.
Research and Collaboration
AAII collaborates with universities, research institutes, governments, and industry partners in Australia and internationally. We welcome opportunities for:
- Academic and industry research collaboration
- Open-source AI development
- Visiting researchers and students
- PhD and postdoctoral research
- Technology translation and real-world deployment
Learn More
Contact
Australian Artificial Intelligence Institute University of Technology Sydney Building 2, Level 12 61 Broadway, Ultimo, NSW 2007, Australia
Australian Artificial Intelligence Institute · University of Technology Sydney