Imperial College London


Faculty of MedicineSchool of Public Health

Honorary Lecturer



+44 (0)20 7594 0716vasa.curcin Website




320Reynolds BuildingCharing Cross Campus





Vasa Curcin is a Lecturer at Health Informatics at King's College London and a Visiting Lecturer at Department of Primary Care and Public Health, Imperial College London. His main web page is here.

He was the healthcare theme coordinator at the London e-Science Centre, while based at the Department of Computing.  He was the Scientific Project Manager of EU TRANSFoRm project, and Technical Lead of CLAHRC Northwest London initiative.

His main research is in the area of provenance-based reproducibility, with specific applications in medical informatics and Big Data analytics. His PhD was on the application of process algebras and other formal models to verification and optimization of scientific workflows. 

Other research interests include:

  • Big Data analytics using scientific workflows
  • Translational research across the whole biomedical spectrum
  • Process models for clinical guidelines

The software tools produced in Vasa's projects are being used by a wider scientific and medical community. These include the WISH tool for model-based clinical data collection and reporting, and the provenance infrastructure for heterogeneous software systems. Software is free of charge, and licensing details are available on request.



Carr E, Bendayan R, Bean D, et al., 2021, Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study, Bmc Medicine, Vol:19

Chapman M, Mumtaz S, Rasmussen LV, et al., 2021, Desiderata for the development of next-generation electronic health record phenotype libraries., Gigascience, Vol:10

Wongkoblap A, Vadillo MA, Curcin V, 2021, Deep Learning With Anaphora Resolution for the Detection of Tweeters With Depression: Algorithm Development and Validation Study., Jmir Ment Health, Vol:8, ISSN:2368-7959

Cabral C, Curtis K, Curcin V, et al., 2021, Challenges to implementing electronic trial data collection in primary care: a qualitative study, Bmc Family Practice, Vol:22

Ford E, Edelman N, Somers L, et al., 2021, Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners, Bmc Medical Informatics and Decision Making, Vol:21, ISSN:1472-6947

More Publications