Biography
Dr Damian Machlanski is a Postdoctoral Scholar at the Causality in Healthcare AI (CHAI) Hub and a Research Associate in Causal AI at the University of Edinburgh, where his work is centred around improving healthcare AI with causality. He obtained his PhD in Computer Science at the University of Essex and is also a former Software Developer. His main research interests are at the interface of causality and machine learning, with a particular focus on the methods for treatment effect estimation and causal graph learning from observational and temporal data, but also the topics of robustness to data shifts, hyperparameters, and their application in healthcare.
Damian’s latest work:
– Sanchez, P. P., Machlanski, D., McDonagh, S., & Tsaftaris, S. A. (2025). Causal Ordering for Structure Learning From Time Series. arXiv preprint arXiv:2510.24639. To appear in Transactions on Machine Learning Research.
– Machlanski, D., Riley, S., Moroshko, E., Butler, K., Dimitrakopoulos, P., Melistas, T., … & Tsaftaris, S. A. (2025). A shift in perspective on causality in domain generalization. arXiv preprint arXiv:2508.12798.
