Welcome!

Hi! I am Damian Machlanski - a Research Associate in Causal AI at the University of Edinburgh and a Postdoctoral Scholar at the Causality in Healthcare AI Hub (CHAI). I am interested in all things related somehow to causality, including mathematical theory, statistical methods, applications with real data, and also the overarching philosophy around it. My research in causality often intersects with machine learning and observational data, leading to my specific interests in causal discovery and causal effect estimation, but also domain generalisation and model selection. Practical applications of those methods to healthcare datasets, which are often temporal in nature, is something I have been also working on since joining CHAI.

Previously to joining CHAI and moving to Edinburgh, I have obtained my PhD in Computer Science at the University of Essex (Colchester). Prior to my PhD studies, I worked as a Software Developer for several years (I still enjoy programming in my work!).

Updates

• Our paper on causal ordering for time series causal discovery has been accepted at TMLR! Stay tuned for details!
• Workshop alert! Come to Edinburgh and discuss causality in healthcare with us. Join us!