I am a Data Scientist at TWG AI, where I design and deliver agentic AI systems that automate end-to-end data science workflows for enterprise clients, from problem framing through deployment.

Previously, I was a Research Scientist at Samsung Research UK, leading the Personalized AI team, where I worked on adapting large language models (LLMs) to resource-constrained environments such as smartphones — including parameter-efficient fine-tuning, federated learning, model merging, continual learning, memory systems, and model compression (see, e.g., our works on hypernetworks, federated learning, model merging, and memory systems).

Before that, I was a Postdoctoral Research Assistant in the Computational Health Informatics group at the University of Oxford, led by Prof. David A. Clifton, where I worked on developing generative models for healthcare, particularly for disease progression modeling and synthetically generating electronic health records (EHRs).

I obtained my PhD from the School of Informatics at the University of Edinburgh under the supervision of Prof. Chris Williams. During my studies, I was based in the Alan Turing Institute where I took part in the Artificial Intelligence for Data Analytics project. As a part of this project, my thesis proposes probabilistic data type inference methods for tabular data. Prior to my PhD, I was a Research Assistant at the at Department of Computer Engineering of Bogazici University, working with Taylan Cemgil.