AI research
AI offers transformative potential to revolutionise knowledge discovery and application with purpose, creating impact through applied and transformational research. Building on the pioneering work by AUT researchers – including groundbreaking development of brain-inspired spiking neural networks and the world-first NeuCube architecture that models how the human brain processes information – our vision is to embrace AI as a catalyst for groundbreaking research across all disciplines.
Current AI research
From healthcare innovation to agricultural technology, these are just some of the AI research projects currently underway at AUT. Discover more of AUT’s research
Fruit measurement and classifications
To support NZ's fruit sector, we apply deep learning and computer vision, making it easier to classify fruits based on a freshness and ripeness analysis.
AI and brain health
By applying cutting-edge AI techniques to acoustic signals, we're developing novel methods to detect and track health conditions through sound patterns.
Simulation and modelling
We employ AI and agent-based modelling to predict system behaviour, with applications in healthcare decision-making and understanding complex network dynamics.
AI in tinnitus
By applying deep learning and brain-inspired spiking neural networks to EEG data we're developing an AI decision tool to predict which tinnitus patients will respond best to specific therapies.
Computer vision
We apply deep learning methods to stereo vision, medical imaging and digital geometry, with specific applications in Māori video understanding and supporting the agricultural industry.
Text processing and machine learning
Using insights from text data, we're developing conversational agents, sentiment analysis systems and recommender technologies for business intelligence.
Natural language processing
We use deep learning methods to develop automated systems for speech recognition, closed captioning and subtitling in both Te Reo Māori and New Zealand English.
Our AI research experts
Below are some of the many researchers across AUT who are exploring the opportunities AI offers to build a smarter, healthier and more connected world.
Akbar Ghobakhlou
Major Leader - Data Science
Catherine Shi
Head of Department - Data Science & AI
Edmund Lai
Associate Head of School - Learning and Teaching
Geri Harris
Programme Director - Business Undergraduate
Mahsa Mohaghegh
Associate Professor Engineering, Computer and Mathematical Sciences
Mangor Pedersen
Associate Professor Psychology and Neuroscience
Maryam Doborjeh
Senior Lecturer Engineering, Computer and Mathematical Sciences
Minh Nguyen
Head of Department of Computer & Information Sciences
Parma Nand
Senior Lecturer Engineering, Computer and Mathematical Sciences
Samaneh Madanian
Associate Professor Engineering, Computer and Mathematical Sciences
Sira Yongchareon
Programme Director Doctoral Studies
Wei Qi Yan
Major Leader - BCIS, Software Development
Weihua Li
Programme Director PG Studies
AUT’s AI approach
At AUT, we believe AI should serve people, not the other way around. That's why we've built our AI strategy on clear principles that put ethics, equity and human connection at the centre of everything we do.
AI in learning and teaching
To ensure that all AUT graduates are confident in an AI-integrated workforce, we’re transforming assessment design, integrating AI across all disciplines, and equipping students and staff with the tools make the most of the opportunities AI offers.
Resources for AUT staff
To help AUT staff embrace the opportunities AI offers, the AI Hub on the staff intranet has a wealth of resources and training opportunities covering how AI can enhance teaching, accelerate research and improve AUT’s operations.