Research interests
Jack's research blends both theoretical and applied aspects of machine learning. His theoretical contributions are focused on continual learning for long-term autonomous agents in multi-agent settings as well as novel unlearning methods for robust, privacy-aware models. The application of his research is ensuring food security and sustainability, helping detect and mitigate risks to the food supply-chain with machine learning techniques.
Department role and responsibilities