I am an AI researcher and founder working on adaptive and human-centred artificial intelligence. My work focuses on developing AI systems that can understand individuals more deeply and adapt to their goals, preferences, expertise, communication style, and changing context over time.

Previously, I was a Senior Research Scientist at Google DeepMind, where I founded and led work on user signals for Gemini. My research focused on modelling user behaviour and preferences, developing user simulators, using simulated users for model evaluation, and improving alignment and personalization during distillation and post-training. I also contributed to the Gemma family of open-weight foundation models.

My broader interests lie at the intersection of artificial intelligence, cognitive science, and the study of mind. I am particularly interested in how computational systems can represent individuals as dynamic, temporally extended persons, and how such representations could enable more adaptive and meaningfully aligned AI.

I am currently building a new AI company in stealth. The work explores how AI systems can move beyond isolated interactions and develop a more persistent understanding of individuals over time. It draws on research in language modelling, personalization, user modelling, cognitive science, evaluation, and post-training. More details will be shared in the future.

I received my PhD in Artificial Intelligence from the University of Edinburgh, supervised by Mirella Lapata and Ivan Titov. My doctoral research focused on Bayesian machine learning, reinforcement learning, and neural methods for abstractive opinion summarization. I previously received an MSc in Artificial Intelligence with distinction from the University of Amsterdam, where I specialized in theoretical machine learning and natural language processing. My research has been published at ACL, EMNLP, NAACL, and related venues.