We have broad research interests across machine learning and its applications. Most applications can be summarized under the umbrella of computational sustainability, a strongly interdisciplinary research area that uses machine learning approaches to address sustainability challenges in Aotearoa and worldwide. For example, our researchers develop models that predict the environmental fate of pollutants, analyse bat calls to track environmental pollution, or analyse air pollution sensor data sets.

Research Area

Bias in Machine Learning

While the awareness for discrimination biases based on genders or ethnicities has grown a lot in recent years, especially in the context of fairness in Machine Learning, many datasets come with certain biases of which the researcher is not aware and hence uses to...

Research Area

Adversarial Learning

Adversarial learning aims to identify weaknesses in machine learning models. The goal is to identify potential problems that cannot be found using traditional evaluation using test sets. It has been used successfully in a wide range of applications, typically...