Edward is a researcher in the Engineering Department at the University of Cambridge. His background is in mathematics and statistics, and his PhD focuses on developing computational models of brain function. He is currently transitioning into research on the security, safety, and robustness of AI systems.

Edward has a keen interest in science outreach and education. Edward has previously worked as a supervisor at the university, teaching undergraduates for a range of courses in mathematics, statistics, and neuroscience. Edward teaches at the Machine Learning for Good (https://www.ml4good.org/) organisation, which runs 10-day bootcamps aiming to give non-specialists an introduction to the field of AI safety and give them an overview of key issues and challenges in the area. He has been heavily involved with designing the curriculum for these camps, as well as developing and delivering course materials.

Recently, in partnership with the Cambridge AI Safety Hub, Edward delivered a lecture series at the Engineering department covering the basics of Large Language Models (LLMs), methods for improving their safety, and critical limitations with these methods. Previously, Edward has delivered courses on other aspects of machine learning, including deep learning and reinforcement learning, all aimed at non-specialists.

Edward believes that safely navigating the development of increasingly advanced AI systems will require informed policy making. Accordingly, he is keen to help policy makers understand at a high-level how AI and machine learning systems work, the ways that they might fail, and how those failures may cause wider societal damage.