A mixture of talks, panel discussions, the opportunity to join in and for Q&A, a PhD forum, and networking

Day One










Mihi Whakatau

Teariki Tuiono (University of Auckland)

Opening Comments

Gillian Dobbie (Conference Chair, University of Auckland) and Albert Bifet (University of Waikato)

Keynote Talk (Recording available)

Charting the course: AI implementation for Public Good
Incentives for use of AI in the public sector with responsible guardrails driving the adoption. Use case identification, privacy by design, and collaboration with the research community for building production grade AI solutions.

Vikash Kumar
Manager, Advanced Analytics & Modelling
Waka Kotahi, New Zealand Transport Agency

Session One (Recording available)

Session Chair - Michael Witbrock (University of Auckland)
(5 minute talks)

Access a recording here.

The Energy Bill of AI (Michael J. Watts, Media Design School)

A time series transformer for forecasting Covid-19 hospitalisations (Jiawei Zhao, Institute of Environmental Science and Research (ESR))

AI and machine learning at VUW --- Overview of CDSAI (Mengjie Zhang, Victoria University of Wellington)

AI Augmented Science (Michael Witbrock, University of Auckland)

Speech Reconstruction for Glottis Impairment: A Non-Invasive Machine Learning Approach (Hamid Sharifzadeh, Unitec Institute of Technology)

Symbolic Regression: Discovering Symbolic Models from the data (Qi Chen, Victoria University of Wellington)

Spatio-Temporal Learning and Spatio-Temporal Associative Memories in Bio/neuro systems, Mathematics and Brain-inspired Neurocomputation (Prof Nikola Kasabov, AUT)



Morning Tea and Poster session

Panel Discussion

Directions for AI policy in New Zealand

Moderator - Ali Knott (Victoria University of Wellington)

Panelists - Tom Barraclough (Co-Founder, Brainbox Institute), Madeline Newman (Executive Director, AI Forum) & Colin Holden (General Manager, System Strategy and Initiatives, Digital Public Service, Department of Internal Affairs)

The panel discussion will delve into the landscape of AI policy in New Zealand, encompassing existing laws as well as extra-legal conventions and practices pertinent to both governmental and commercial AI usage. On the governmental side, we will consider how AI might best be used to modernise and improve the efficiency of our public services, and how public services should manage the risks associated with AI. On the research and commercial side, we will ask what’s needed for AI to flourish in the science/research environment - and how this flourishing can lead to meaningful commercialisation/startup opportunities. 





Sponsor Presentation (Recording available)

Richard Green (University of Canterbury)

See the unseen – we cannot automate what we cannot see in agriculture and aquaculture
Our research is interested in real-world applications, such as rapid data reduction of petabytes of data from scanning orchards or vineyards from sub-mm under-canopy/underwater proximal sensing. We cannot automate what we cannot see – so our recent breakthroughs with NeRF and Gaussian splatting is helping to solve leaf occlusion to enable a rapid uptake of agricultural automation. I will describe our contributions across these research areas, including recent autonomous systems research into drones pruning forests, robots pruning vineyards, autonomous underwater vehicles (AUVs) inspecting mussel lines to detect invasive biofouling species and AUVs mapping the seabed to locate scallops. We will also discuss the challenges that remain and so propose potential directions for future work.

Lunch and Poster session

Session Two (Recording available)

Session Chair - Julian Maclaren (Nelson AI)
(5 minute talks)

Access a recording here.

AI for anomaly detection: from biosecurity to climate (Dr. Varvara Vetrova, University of Canterbury) 

Can deep learning improve harvest decisions in aquaculture? (Julian Maclaren, Nelson AI Institute)

Comparative Analysis of Predictive Models for Daily PM10 Concentration Time Series in Auckland Urban Area: A Quasi-Experimental Exploration (Dr Sara Zandi, New Zealand Skills and Education Group (NZSEG))

Deep Learning in Global Weather Forecasting (Gemma Mason, NIWA)

Collecting an aquaculture dataset using an accessible multiplatform phone app (Dana Lambert, Harvest Hub)

Dynamic Systems in Machine Learning: Navigating Continual Adaptation in Evolving Environments (Yun Sing Koh, University of Auckland)

Evolutionary Machine Learning Approaches and Applications (Bing Xue, Victoria University of Wellington)

Federated Learning-Enabled AI-Generated Content in Vehicular Internet of Things (VIoT) (William Liu, Otago Polytechnic Auckland International Campus (OPAIC))

Exploiting image classification explanations for object detection, segmentation and (improved) classification (Nick Lim, University of Waikato)

Optokinetic Response Detection Using Self-Supervised and Pre-training Model on Eye Tracking Video (Mohammad Norouzifard, University of Auckland)

TAIAO – Green AI in Green Aotearoa (Albert Bifet, University of Waikato)





Sponsor Presentation (Recording available)

Yun Sing Koh (University of Auckland)

AI Initiatives at the University of Auckland

Afternoon Tea

Panel Discussion

Generative Reo Māori AI
Moderator - Te Taka Keegan (University of Waikato)

Panelists - Lynell Tuffery Huria (Tumu Whakahaere | Managing Partner, Kahui Legal), Tūreiti Keith (Senior Data Scientist, Te Hiku Media), Ria Tomoana (Research Manager, Te Mātāwai) & Basil Keane (Te Mātāwai) & Te Mihinga Kōmene (PhD Ākonga & Contractor, Ko Te Mihinga Ahau)

The panel will engage in a comprehensive exploration of the implications surrounding generative reo Māori AI, particularly examining concerns regarding its potential to either preserve or inadvertently colonize te reo Māori, the complexities of Māori data sovereignty in the face of Big Tech influence, the disparities between users and makers of AI tools, and the nuanced distinction between Māori data sovereignty and digital sovereignty. Additionally, the discussion will address intellectual property concerns surrounding data usage and output, with a commitment to fostering an inclusive dialogue that allows for the organic exploration of various perspectives and potential actions to safeguard Māori interests while embracing technological advancements.


Session Three (Recording available)

Session Chair - William Liu (Otago Polytechnic)
(5 minute talks)

Access a recording here.

Large Population Model for Complex Health Behaviour Simulation (Sijin Zhang, Institute of Environmental Science and Research)

Learning from Data Streams versus Continual Learning (Bernhard Pfahringer, University of Waikato)

Learning to Schedule Manufacturing Jobs via Reinforcement Learning (Yuqian Lu, University of Auckland)

Legal Regulation of AI - Missing the Mark? (Gay Morgan, University of Waikato)

Machine learning for emergency medical dispatch (Yi Mei, Victoria University of Wellington)

Vehicle real time image collection for pavement defects identification (Heyang (Thomas) Li, University of Canterbury)

Forecasting the longitudinal tree radial growth data with Deep Learning methods: A case study (Guilherme Weigert Cassales, University of Waikato)

Genetic Programming and Machine Learning for Job Shop Scheduling (Fangfang Zhang, Victoria University of Wellington)

NEXT: Operational Nowcasting System for Wind and Solar Power in New Zealand
(Tristan Meyers, NIWA)

Introducing Monica an Ai Co-Pilot for Central Monitoring Stations, Security Operations Centres and you (Felix Marattukalam, University of Auckland)

Ensemble modelling provides robust time series forecasting for hospitalization rates related to severe respiratory diseases in Auckland (Steffen Albrecht, University of Auckland)





Wrap up day one

Gillian Dobbie (Conference Chair, University of Auckland)

End of Day One

Dinner and Drinks

We will have a short quiz at the start of dinner based on talks and posters

Day Two






Welcome and opening comments

Richard Green (University of Canterbury)

Session One (concurrent)

Panel discussion - AI Research: How to attract funding
The panelists, having all had success attracting funding across a range of funds, are at different stages in their careers and will talk about funding in Aotearoa New Zealand including what makes a successful funding bid.

Moderator - Gillian Dobbie (University of Auckland)

Panelists - Mengjie Zhang (Victoria University of Wellington), Richard Green (University of Canterbury), & Qi Chen (Victoria University of Wellington)

Student lightning* talks on posters with facilitated Q&A

  • Ding Ning (University of Canterbury)

  • Olivier Graffeuille (University of Auckland)

  • Simna Rassak (ESR)

  • Siyao Lu (University of Auckland)

Facilitator(s) - Nuwan Gunasekara (University of Waikato) and Fang Fang Zhang (Victoria University of Wellington)



Morning Tea and Poster Session

Session Two (Recording available)

Talk - Data Ethics and Innovation: Practical Steps
Emma MacDonald (Centre for Data Ethics and Innovation, Ministry of Statistics)

Mentoring session with senior researchers

An informal session where four PhD researchers will be paired with a senior researcher to discuss topics related to research life, such as identifying research topics, research communication, time management, and work-life balance.

Facilitator(s) - Nuwan Gunasekara (University of Waikato) and Fang Fang Zhang (Victoria University of Wellington)





Paying homage to Ian H. Witten

Albert Bifet (University of Waikato)

Access a recording here.

Lunch and Poster session

Panel Discussion (Recording available)

AI's impact on society

Moderator(s) - Albert Bifet (University of Waikato) and Phil Mourot (University of Waikato)

Panelists - Daniel Wilson (University of Auckland), Emma MacDonald (Centre for Data Ethics and Innovation, Ministry of Statistics), Jonathan Kim (Principal Software Engineer, Callaghan Innovation) and Paul Seiler (Catalyst Cloud)

This panel will bring together experts to discuss the profound impact of AI on society. We will explore the ethical, economic, and social implications of artificial intelligence, examining both the positive transformations and the challenges it poses. From reshaping industries to influencing policy decisions, this discussion will provide a comprehensive overview of how AI is altering our world.






Closing comments

Gillian Dobbie (Conference Chair, University of Auckland)

Karakia Whakamutunga

Daniel Wilson (University of Auckland)

Conference end


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