Belen Martin-Barragan

• Reader in Management Science.
• Management Science and Business Economics Research Champion.
• Deputy director of research (Ethics and Integrity).

Belen Martín-Barragán is Reader in Management Science at The University of Edinburgh Business School. Her research lies at the interface between Data Science and Mathematical Programming, with a special interest on Explainable Artificial Intelligence. In a board sense, her research interests focus on using or developing variants of Operational Research techniques and applying them to data analysis problems, such as classification and clustering. Her work has appeared in a variety of top-ranked journals such as European Journal of Operational Research, Risk Analysis, INFORMS Journal on Computing, Discrete Applied Mathematics, Computers and Operations Research. She is also contributed to other areas such as statistics (Journal of Applied Statistics) and economics (Economic Modelling). She has been PI of the EPSRC-funded project “Optimisation Models for Interpretable Analytics”.

My research lies at the interface between Machine Learning and Mathematical Programming. In a board sense, I am interested on using or developing variants of Operational Research techniques and applying them to data analysis problems, such as classification and clustering. I use those tools for creating intrinsically interpretable machine learning models, hence contributing to explainable artificial intelligence (XAI). I also apply them to other areas such as inventory and routing.

Belen Martin-Barragan discusses her research in Machine Learning, focusing on creating highly predictive models that are easier to explain, ensuring individuals' rights to receive explanations for significant decisions in the era of artificial intelligence.