My project is advancing work on the value alignment process in AI, which is how we build AI systems to not just solve problems, but do so in a way that aligns with our social and moral values. In my project I will be characterising the value alignment process between humans and AI based on research to date, and using this understanding to develop methods of assessing alignment between humans and autonomous agents using logical reasoning over knowledge maps.

As a science communications ambassador for the computer science department, I translate complex research into compelling narratives for the public. Passionate about bridging the knowledge gap between academia and society, I strive to promote informed discourse on the transformative power of technology.

Explored methodologies within Explainable AI and delved into the nuances of reinforcement learning. Executed hands-on experiments in training reinforcement learning models, specifically focusing on game-playing scenarios. Authored comprehensive write-ups detailing research insights and experiment outcomes. Effectively communicated findings to both the team and senior management through engaging presentations.

Revamped operational processes, reducing a three-day task to a streamlined two-hour version with a user-friendly output, contributing to efficiency and effectiveness. Documented and communicated these improved processes to foster collaboration with team managers and users. Actively assessed critical outcomes of model outputs, translating and conveying findings to both internal and external stakeholders. Orchestrated seamless hand-ins for audits and facilitated smooth processes across the reporting team.