Workshop speakers

TAIAO Workshop 2023 is just two weeks away, and we are excited to meet you! To start off, allow us to introduce some of our speakers. Here are four of our team members who will be presenting their work at the workshop:

Jack Julian, PhD Student, University of Auckland

Anomaly Detection with Continual Learning for Maritime Trajectories

Jack studies irregular movements of maritime vessels, which can indicate illegal fishing activity, oil spills and potential biosecurity risks. With the help of continual learning techniques, these anomalies can be detected in real time to identify and prevent environmental hazards.

Guilherme Cassales, Postdoctoral Research Fellow, University of Waikato

Forecasting Plantation Forests Growth: Current State and Future Directions

In plantation forests, where returns take more than a decade to materialize, proactive planning is crucial. Current technologies can often provide real-time spatio-temporal data, which require appropriate methods to successfully extract knowledge and use these large and complex databases. In this talk Guilherme will discuss the utilization of Machine Learning (ML) tools to optimize resource allocation with forestry hydrology data and the exciting opportunities for future research, particularly related to the analysis of intricate edaphoclimatic data collected throughout the forests.

Olivier Graffueille, PhD Student, University of Auckland

Exploring Machine Learning methods for Water Quality Remote Sensing

Olivier’s research focuses on using machine learning techniques for water quality remote sensing. He explores characteristics of this problem from a data perspective, which allows him to link these to relevant machine learning ideas. This allows him to better model this important environmental problem, while also advancing fundamental machine learning research.

Ding Ning, PhD Student, University of Canterbury

Graph-Based Deep Learning for Sea Surface Temperature Anomaly Forecasts

Ding will talk about his research on using graph re-sampling on the gridded ERA5 product and a graph neural network for learning from large graphs that evolve over time, to forecast global monthly mean sea surface temperatures and their anomalies.

We will be sharing more information about our speakers in the coming days. Registration is ongoing, so come and join us! You can register here, and please don't hesitate to share this invitation with your team and partners.

Venue: TCBD.2.03, The University of Waikato, Tauranga Campus, 101 Durham Street

Date: Thursday 24 August 2023

Time: 9am - 5pm