I currently work on a collaboration with researchers at the Future of Humanity Institute to develop safe Machine Learning algorithms. We are developing Bayesian Reinforcement Learning methods using the notion of pessimism. Previous work has shown that, given a safe mentor, an agent can be trained to complete a task without causing catastrophic events and exceed its mentor’s performance. I now investigate these agents empirically. The work is funded by a grant from the Effective Altruism Long Term Future fund; I am very grateful to all the donors that made this possible.
Because I believe aligning AI with human values is a priority in a rapidly advancing field, I jointly organise the Cambridge AI Safety Community. We run events and meetups that bring-together those who are passionate about reducing existential risk from misaligned advanced AI, to support their interest and future career.
You can also catch me bouldering, performing with the guitar whenever I get the chance, and keeping active in various ways! Otherwise, I enjoy spending time in the Effective Altruism community to explore other opportunities to use my time and resources to do good.
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I’m most excited to get back to the continuation of my Master’s project. I developed a promising theoretical analysis of smoothed labels during the project, and therefore aim to to introduce Bayesian Label Smoothing.
Check out my work on GitHub
Other work on GitHub includes OpenAI Spinning Up (Reinforcement Learning) implementations, Hack Cambridge Hackathon projects, and the Gaussian Processing tools repository contributing to my publication.
Undergraduate Summer Research Placement, Culham Centre for Fusion Energy, 2017