I primarily specialise in explainable and interdisciplinary artificial intelligence. My research explores AI's social and ethical implications, with applications in ecology, legal decision-making, and more.

I also have interests in "fundamental” machine learning, such as genetic programming, unsupervised learning (nonlinear dimensionality reduction), and aspects of deep learning, such as embedding/manifold learning methods.