Professor of Operational Research
Christina has a background in maths and physics. From being a post-doctoral physicist, she made the leap into mathematics applied to health care in 2005 and is now Director of CORU and Professor of Operational Research. Her recent work has focused paediatric intensive care and outcomes after children’s heart surgery. She was a 2016-17 Harkness fellow in Health Policy and Practice, based between Brigham and Women’s Hospital (Harvard) and the Institute for Healthcare Improvement in Boston, US where she worked on understanding politicians’ priorities for US health policy and on implementation of I.T. systems. She is passionate about using information to help people improve delivery of healthcare.
CORU's Deputy Director
Associate Professor of Operational Research
Sonya has a PhD in physics and worked in the Government OR Services before joining CORU in 2009 from the Department of Health. She has worked on a wide range of projects relating to service delivery and innovation in health and social care, health protection policy and global health. In 2013 she was awarded a Health Foundation Improvement Science Fellowship. Her current interests include: combining quantitative and qualitative OR methods to improve services that span multiple sectors; linking national datasets to support quality improvement in services for congenital heart disease; and enhancing the effectiveness of OR in contributing to improvement.
Professor of Operational Research
Former Director of the unit (2007-2017), Martin joined CORU in 1996 having gained a PhD in high-energy physics. Martin has experience of working on a wide variety of problems in health and health care, spanning many clinical areas. Actively involved in many aspects of CORU's current research, he is committed to assisting those planning, delivering or evaluating health services by developing, adapting and applying operational research techniques.
Associate Professor of Operational Research
Alex is an applied mathematician working on uncertainty quantification, Bayesian inference and model calibration. He is an EPSRC Fellow leading DATA-CENTRIC: Developing AccounTAble Computational Engineering Through Robust InferenCe. In this research, he is developing Bayesian techniques for numerical methods that quantify uncertainty due to computation. His continuous involvement with industrial partners has led to several projects with engineering companies, government bodies and SMEs. He has organised four study groups to strengthen the relationship between academia and industry. Alex joined CORU in September 2019, where he is developing statistical and computational methods to analyse large data sets and thus support clinical decision making.
Senior Research Associate
Luca has a background in Industrial Engineering and Operational Research techniques gained during his Bachelor’s and Master’s degrees at Sapienza University of Rome. In 2008 he moved to France where he earned his PhD in Genomics and Bioinformatics dealing with machine learning and dynamical modelling approaches to identify targets for cancer therapy. In 2014 he was appointed as Research Associate at CORU where he applies quantitative methods to support health protection policy and to improve performance of healthcare systems.
Ferran has a PhD in Mathematics and a MSc in Statistics and Operational Research. He did part of his research on Geometry and Statistics applied to Computer Vision. Since May 2013, he has been interested in methodological and applied research related to health and social care. He is very enthusiastic about having joined CORU in February 2019, where he is currently doing research on Linking audit and national datasets in congenital heart services for quality improvement.
Zella is an academic data scientist. She gained her PhD in Organizational Psychology from Birkbeck College. Her academic career began with 15 years in business schools. Her work on human resources, careers and networks has been published in top business journals. In 2007 she was awarded a fellowship of the Advanced Institute of Management. In 2014 she took time out of academia to co-found a training company which has become commercially successful. In 2016, concerned about healthcare in ageing societies, she changed fields to focus on health data research. She is currently developing machine learning models to help bed-planners at UCLH predict which patients will be admitted from the emergency department.
Sam is a research fellow in Statistics. His research interests focus on the uncertainty quantification and statistical emulation of computer models, Bayes linear methods and history matching. His research application areas have been broad, spanning defence threat reduction, epidemiology, medical imaging and systems biology. His current application focus involves working on a project to improve care for intensive care unit patients.
Senior Finance Administrator
Ruksana has a background in Education Finance. She graduated from City University in 2001 after gaining a honours degree in Management and Systems. She joined an accountancy firm BDO before embarking on a career at a Further Education (FE) College within their Core Finance dept. Ruksana has since held a variety of financial management roles within different FE institutions, joining CORU in 2017. She has a passion for working in the public sector and education finance services.
Senior Research Administrator
Following a degree in Zoology at University of Wales-Bangor, Julie completed her training to become a HCPC registered Biomedical Scientist in histology. Whilst working in biomedical science, Julie completed her MSc in Epidemiology at the London School of Hygiene & Tropical Medicine before taking a Research Assistant post at the Gynaecological Cancer Research Centre, UCL in 2014. From January 2017 she worked on the British Women’s Heart and Health Study at the Institute of Health Informatics, and joined CORU in March 2018 as the study coordinator for Linking audit and national datasets in congenital heart services for quality improvement (LAUNCHES).
Qi has a background in engineering and gained her PhD in signal processing and communications from Edinburgh University. Since 2016, she has been interested in developing and applying statistical methodologies to health care data, and her main research experience focused on the statistical modelling of circadian rhythm time series to answer statistical and mathematical questions on chronobiology. Qi joined Coru in April 2021, where she is working on the long-term outcomes of survival and re-operation amongst children born with congenital heart disease.
Honorary Senior Research Fellow
Tom is a Principal Research Fellow in Operational Research and Data Science at the University of Southampton. He is also Director of Data Science for the NIHR Collaboration in Leadership and Applied Health Research (CLAHRC) Wessex. Tom is a methodologist with expertise is in applying computer simulation methods, mathematical modelling and machine learning in health service delivery. In particular, his research has used modelling and analysis to help the NHS improve stroke thrombolysis services.
Amalia has a background in both physics and mathematics. After completing her BSc at the University of Richmond, she took time off from academia and worked at a healthcare software company for two years. There, she worked closely with several health care organizations in regards to patient movement and financial assistance. In 2020, she completed her MSc in physics at Imperial College of London with a focus on astrophysics. During her PhD, she hopes to combine her knowledge of electronic health record systems (EHRS) with operational research techniques to improve NHS services.
Hugh completed his undergraduate degree in mathematics at the University of Warwick in 2019, with his final year integrated masters project focussing on quantum algorithms. Following this, he spent a year working as a mathematics tutor at a secondary school. Now returning to academia to undertake a PhD, he hopes to develop structural reliability Bayesian methods and data science techniques that can be applied to intensive care unit data.