Albert previously worked at Huawei Noah's Ark Lab in Hong Kong, Yahoo Labs in Barcelona, and UPC BarcelonaTech. He is the co-author of a book on Machine Learning from Data Streams published at MIT Press. He is one of the leaders of MOA, scikit-multiflow and Apache SAMOA for implementing algorithms and running experiments for online learning from evolving data streams. He was serving as Co-Chair of the Industrial track of IEEE MDM 2016, ECML PKDD 2015, and as Co-Chair of KDD BigMine (2019-2012), and ACM SAC Data Streams Track (2021-2012).

Karin completed a PhD in physical oceanography at Dalhousie University in Canada and came to New Zealand on a Natural Science and Engineering Council of Canada international postdoctoral fellowship. Karin then worked at the National Institute of Water and Atmospheric Research. In 2001, Karin moved to the University of Waikato, where she has taken on a number of roles such as Deputy Head of School, Assistant Dean, and Director of the Environmental Research Institute. Karin’s current work has gradually shifted from nearshore physics (beaches) to working more on ecosystem-geomorphology interactions, natural hazards and in estuaries. This is mainly due to working with some fabulous collaborators along the way that have convinced Karin to solve some different problems.

Greg Pearson is a meteorologist with 25 years’ experience working at MetService and its subsidiary MetOceans Solutions. Greg has a background in running local area numerical weather prediction models, as well as applying statistical methods to improve model output. He has worked on a large number of projects including producing severe weather guidance for New Zealand’s National Weather Service, building forecast systems for European wind farms and running bespoke models for clients in the aviation, marine, energy and television sectors.

Yun Sing Koh is an Associate Professor at the School of Computer Science, The University of Auckland, New Zealand. Her research is in the area of machine learning. Within the broad research realm, she is currently focusing on three strands of research: data stream mining, lifelong and transfer learning, and pattern mining. She has published more than 100 research papers in this field at top venues.

She has been active in the research community including serving as the General Chair at the IEEE International Conference on Data Mining 2021, Workshop Chair at the ECML 2021, Program Co-Chair of the Australasian Data Mining Conference 2018 and as the Workshop Chair for the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining.

Jannat is a CPA and former CIO with a Masters in Digital Business from the University of Waikato and a focus on leveraging technology in innovative ways to benefit people and planet. Jannat's initial career was in the financial services industry leading mid to large-scale technology adoption initiatives, following which she spent more than a decade in the vocational education sector. More recently Jannat has been involved with initiatives supporting digital inclusion and enablement.

Jannat is the Associate Director at the University of Waikato’s Artificial Intelligence Institute.

Phil Mourot has been working in Natural Hazards for more than 20 years, across different disciplines such as electronics, geoscience, computer science, geophysics and seismology, and completed a PhD in applied seismology in France to predict rockfalls and landslides (Grenoble). Phil is involved in the TAIAO project and with a foot in local government and another foot in research he is able undertake research projects that align with local government issues and focus on helping New Zealand be a more resilient nation. Phil’s current research focuses on predicting the impact of floods using machine learning.