Kate Highnam is a postgraduate researcher in the intersection of machine learning and cyber security at Imperial College London. Her PhD explores using domain adaptation and continual learning methods for intrusion detection systems. Based on her professional experience prior to Imperial, Kate aims to enhance the robustness of black-box machine learning models in production environments. She welcomes further experience in control engineering/learning, transfer learning, continual learning, topological data analysis, optimal transport, Bayesian nonparametric modeling, and all things cybersecurity.