As an initiative supported by the Ministry of Business, Innovation and Employment (MBIE), TAIAO is committed to promoting and facilitating the adoption of artificial intelligence (AI) and data science in New Zealand's environmental sector.
In this newsletter, you’ll find:
Delphitech wins global award
Hackathon highlights
Introducing TAIAO Talks
Project Team spotlight
What have we been up to
What’s coming up
Team Delphitech wins global award
We are pleased to share that Léa Cassé and the DelphiQ team were recently announced as the winners of the Global Industry Challenge – World Bank track at the Quantum World Congress 2025 for their innovative solution to improving insurance for communities exposed to flooding.
In addition to funding Léa's PHD research on quantum models for environmental data streams, the DelphiQ team were able to use TAIAO’s open online datasets of New Zealand rivers and rainfall, as well as the expertise of its researchers to build and test this novel approach to one of the World Bank’s pressing challenges.
Their recognition on this global stage underlines how TAIAO’s mission, advancing open science for environmental time-series data, can extend far beyond New Zealand. By supporting researchers, enabling access to critical datasets, and fostering collaboration, TAIAO has helped position New Zealand research at the forefront of the global quantum innovation landscape.
Hackathon Highlights
In late August, 17 participants joined the TAIAO team for the Waikato Hackathon to develop AI-powered solutions to real-world environmental challenges.
This year’s event was centered on the theme of strengthening partnerships between industry, professionals, and the community. AI technologies played a central role in the hackathon, with agentic systems and large language models (LLMs) integrated into many of the solutions.
The winning group, Team Gallagher, proposed a project called "Recraft AI: Turning Commercial Waste into Community Treasure". The project aimed to reduce and upcycle construction waste through community-led initiatives. Other great ideas and projects included mental wellness check-in tools designed to support vulnerable communities.
Project Team Spotlight
Yun Sing Koh is a Professor of Computer Science at the University of Auckland and Director of the Centre of Machine Learning for Social Good.
Within TAIAO, she leads the work package on anomaly detection and extreme events. Her research focuses on developing machine learning methods that can detect and adapt to unexpected changes in dynamic environments. Current projects include identifying anomalies in water quality across New Zealand lakes, monitoring irregularities in ship routing, and detecting anomalies in air quality data.
Beyond TAIAO, Yun Sing has published extensively in leading international venues and received national and international recognition for her contributions to machine learning. She is committed to building strong interdisciplinary collaborations, linking AI research with environmental science to address urgent challenges in sustainability and climate resilience.
A year in review
Over the past year, TAIAO has continued to grow as a leading hub for environmental data science in Aotearoa New Zealand. Our community platform has expanded to over 400 registered users and more than 1,100 followers across our platforms, reflecting a strong and engaged network committed to open-source collaboration, data sovereignty, and Vision Mātauranga.
Between August 2024 and August 2025, we:
shared new datasets, tutorials, and software, fostering capacity-building and supporting researchers, students, and practitioners nationwide
advanced methods in machine learning for data streams, anomalies, and deep learning, with several papers published at top international venues
celebrated the completion of several PhDs, contributing new knowledge in areas such as flood prediction, climate anomalies, and water quality monitoring
began exploring the potential of quantum machine learning, opening up opportunities for the next generation of environmental data science methods
actively supported several exciting networking and conference initiatives, and
supported case studies which have continued to drive impact, with progress in flood prediction, forest monitoring, under-sea habitat annotation, kiwi conservation, and species classification.
You can find out more about what we’ve been up to on our website: www.taiao.net.
What's coming up?
Artificial Intelligence for Earth and Environmental Science workshop
TAIAO is hosting the AI for Environmental and Ecological Sustainability (AIEES) workshop from 17–21 November in Wellington. This event will explore how artificial intelligence can help tackle major environmental challenges like climate change, biodiversity loss, and resource depletion.
The workshop will bring together AI researchers, environmental scientists, and industry professionals to share ideas, collaborate, and submit research papers on topics at the intersection of AI and environmental science.
We’ll have more to share about this in next month's e-newsletter.
Ngā mihi,
The TAIAO team
