Imperial College London


Faculty of MedicineDepartment of Surgery & Cancer

Clinical Research Fellow







Commonwealth BuildingHammersmith Campus





I am an academic Anaesthetic and Critical Care doctor, and a Wellcome Trust 4i Clinical PhD Fellow at Imperial.

My research aims at early diagnosis and improved treatment of critical illness, using methods from Bayesian statistics and machine learning. I am particularly interested in merging these methods with physiological models to provide bedside decision support, in disease heterogeneity, and in the role of uncertainty in clinical decision-making.

My recent work includes representing ICU patients’ status using time-series data to allow prediction of clinical events, exploiting structured knowledge for automated clinical coding, mortality risk prediction for patients undergoing emergency laparotomy, and phenotyping of ventilator-associated pneumonia in electronic health records.

I am an NHS England Clinical Entrepreneurship Fellow, a fellow of the Faculty of Clinical Informatics and a member of the core advisory group for the Academic Health Science Networks Artificial Intelligence Programme. I co-founded and lecture on the Data Science for Doctors courses, and previously co-founded the medical education startup T-Log.

See my ResearchGateTwitter or LinkedIn profiles for more information, or get in touch via

Selected publications

Catling F, Wolff AH. Temporal convolutional networks allow early prediction of events in critical care. J Am Med Inform Assoc 2020;27:355–65.

Catling F, Spithourakis GP, Riedel S. Towards automated clinical coding. Int J Med Inform 2018;120:50–61.