With the rise of machine learning across sectors in recent times, one of the major challenges is the disconnect between theory and application. In many cases, methods have to be tailored to given requirements, for example due to legislative frameworks or specifics of the available data. At the same time, practitioners often lack an in-depth overview of current methodological developments, sometimes with no clear point of contact to get insights and recommendations.

The Domain-Driven Machine Learning (2DML) Lab, housed in the University of Edinburgh Business School, bridges this gap as a “home” for methodology-oriented work focussed on specific areas of application, aiming to encourage interdisciplinary collaboration. We welcome projects from all research fields, with relevant domain knowledge contributed by colleagues contacting us for support. Similarly, we are open to consulting projects from a variety of industry sectors.