Dr Sabina Sloman PhD

• Member of the European Laboratory for Learning and Intelligent Systems (ELLIS) Society
• PhD in Social and Decision Sciences, Carnegie Mellon University, 2022
• BA in Economics, McGill University, 2015

Sabina received her PhD in Social and Decision Sciences (Concentration in Cognitive Decision Sciences) in 2022 from Carnegie Mellon University, advised by Dr Daniel Oppenheimer. Her dissertation investigated the robustness of Bayesian experimental design to misspecification.

From 2023 to 2026, she was a postdoc with the Manchester Centre for AI Fundamentals in the Department of Computer Science at the University of Manchester, supervised by Dr Samuel Kaski.

She joined the Statistics and Data Science Group at University of Birmingham as an Assistant Professor in 2026.

Dr Sloman is currently accepting doctoral students to work in the areas of Bayesian inference and/or probabilistic machine learning, on topics that may include:

-Bayesian experimental design
-Bayesian transfer learning
-Bayesian inverse problems
-Uncertainty quantification
-Generalised Bayesian inference
-Scientific applications

Prospective applicants are encouraged to get in touch via email.

During her PhD, Sabina worked on methods for robust cognitive modelling. Motivated by the often challenging problems of estimation and inference that arise in disciplines like cognitive science, her work aims to facilitate reliable statistical inference in data-scarce and changing environments. She maintains a strong interest in the applications of her work to scientific theory and practice.

Current research themes include:

• Robust Bayesian experimental design: What experimental design principles enable robustness to model misspecification?
• Model selection/model parsimony: What is the relationship between the expressivity of a model class and the predictive performance of the model selected from that class?
• Transfer learning: What forms of additional data or feedback enable robustness to distribution shift?