Current PhD Candidates
Asem Abdulaziz - Data Science for Cancer Pathway Analysis
Baoru Huang - Development of surgical navigational and visualisation tools to enable surgeons to intuitively use a “tethered laparoscopic molecular probe” and optical biopsy device for accurate identification of prostate cancer and image-guided surgery
Daniela Rodrigues - Evaluation of digital-first models of care using routinely collected data
Jackie Van Dael - Improving the analysis and use of patient complaints for quality monitoring in the English National Health Service (NHS)
Katelyn Smalley - Patient Academy: Empowering Patients to Self-Manage
Lisa Freise - Engaging patients in their care through electronic record access
Marcos Manhaes - Improving safety culture through digital enabled networks: a novel patient safety strategy
Mustafa Khanbhai - Exploring the opportunities and challenges of measuring patient experience data in real-time using digital technology
Sneha Jha - Application of Machine Learning to defining problems and diagnosis from the interoperable electronic patient record
Completed PhD Candidates
- Archie Hughes Hallett - The Development of an Image Enhanced Operating Environment in Robotic Partial Nephrectomy
- Bushra Siddiqi - The Application of Process Mining to Care Pathway Analysis in the NHS
- James Dilley - Evaluating the opportunities for image guidance as a surgical decision-support technology to improve
- Jochem Caris - The role of the patient in evaluating Quality of Care
- Kelsey Flott - Improving the usefulness and use of patient experience feedback
- Mafalda Camara - Patient-Specific Simulation Environment for Surgical Planning and Preoperative Rehearsal
- Sabine Vuik - The application of data-driven population segmentation to design patient-centred integrated care
Funded Research Programmes

Patient Experience
Scale, spread and embed - Using natural language processing of free-text patient experience
Research Student Supervision
Dawda,S, Image guidance in patient-specific surgical simulation
Khanbhai,M, Using Natural Language Processing on patient experience feedback for real-time benefit