Russel holds a Master of Science in Machine Learning from the University of Birmingham.
Russel is a Research Fellow at the Institute for Data and AI (IDAI). His research focuses on data-efficient learning, interpretability, and the mechanistic understanding of alignment in large language models, alongside metascience and human-model disagreement.
As an IDAI Research Fellow, he helps to shape research priorities and supports data-intensive research proposals across the University.
Russel's individual research investigates the core challenges of model alignment and factuality. This includes analysing the sources of human-model disagreement in the data used to align large language models and contributing to the development of optimised fact-checking pipelines. This work is complemented by interdisciplinary collaborations. With colleagues in Psychology, he has explored the differences between human and model reasoning, leading to a system for automating the scoring of psychological assessments. With a team in Education, Russel's work involved analysing the impact of student-AI interactions.
Russel's Masters dissertation focused on evaluating adversarial alignment subversion in large language models. H Bachelor of Technology in Electronics and Communications Engineering; his dissertation involved developing a deep learning system for the pixel-wise classification of land-use from satellite imagery. Russel's prior research experience includes developing machine learning models for applications in satellite imaging and computational histopathology.
He joined IDAI at the University of Birmingham in 2025.