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Prior to completing a PhD in Reinforcement Learning (RL) in 2024, I worked for 18+ years as a highly respected enterprise developer-analyst in multi-national companies. I therefore possess a deep understanding and considerable experience with enterprise project environments and key business processes. I am a strong communicator, having represented development as technical team lead within cross-functional projects. I am results-oriented, have worked successfully within the agile framework and coming from a pharmaceutical background I care about the quality and societal impact of my work.

My PhD equipped me with a strong background in Machine Learning (ML) methods with experience implementing and extending ML, especially RL, algorithms. I am comfortable analysing data, debugging machine learning algorithms, building tools for analysis and logging while making use of the latest features in existing frameworks and tools. Having previously worked extensively with high profile production systems, I code in a production-aware manner. I am a strong advocate of good design and development practices that I encourage in all teams I work with.

During my PhD I was fortunate to work with a diverse range of people, some of whom I now collaborate with on on-going research initiatives. I have both tutored and mentored students, run workshops on coding and deep dives and given talks on ML and RL.