Contact information
Websites
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Centre for Statistics in Medicine
Research Group
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STAR Programme
STAR - Support and Treatment After Replacement
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ATLAS Programme
ATLAS -Enhanced Recovery for Arthroplasty Patients
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EHDEN
European Health Data & Evidence Network
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OHDSI
Observational Health Data Sciences and Informatics
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National Geographic Society
Early Career Explorer
Sara Khalid
BE, MSc (Oxon), DPhil
University Research Lecturer, Senior Research Associate in Biomedical Data Science
- Machine Learning Lead - Pharmaco-device Epidemiology Group, Centre for Statistics in Medicine
- National Geographic Explorer - Tracking Plastic Pollution with Remote Monitoring and Machine Learning
- Ambassador for Women in Data Science - University of Oxford
Health Informatics, Intelligent Patient Monitoring, Planetary Health
Sara leads the Machine Learning and Big Data Analytics branch of the Musculoskeletal Pharmaco-epidemiology group in NDORMS, which she joined in 2016. She was previously based at the Institute of Biomedical Engineering (IBME) as a postdoctoral researcher in the Biomedical Image Analysis Lab, and in the Biomedical Signal Processing and Computational Health Informatics Lab. Her research extends into conservation research. She is a National Geographic Early Career Explorer having secured a grant for using machine learning and remote monitoring for tracking plastic pollution from land to sea.
Sara completed her DPhil in Engineering Science at the IBME, University of Oxford, as a Rhodes Scholar. Prior to that she received a Distinction for her MSc in Biomedical Engineering from the University of Oxford in 2009, as a Qualcomm Scholar. In 2007 she graduated with a BE in Electronics Engineering from the National University of Sciences and Technology in Karachi, Pakistan.
Her research interests include signal processing and machine learning, with applications in health informatics such as patient monitoring, telehealth, and observational research.
Sara's thesis explored Bayesian methods for providing early warning of patient deterioration, using time-series physiological data, and developed machine learning methods for multi-class classification of patient abnormalities using vital-sign data acquired from a large study with collaborators in the University of Pittsburgh Medical Centre. Sara led the data collection and statistical analysis of the multi-phase Cancer Hospital Study undertaken in the Cancer Hospital in Oxford, UK.
Teaching and Supervision
Sara teaches data science and machine learning for healthcare research at NDORMS. She is the trainer of the University-wide course "Statistical Learning in R" in collaboration with The Oxford e-Research Centre Advanced Research Computing and the Computer Science Department. She is also a faculty member at the NIHR BRC course "Data analysis: Statistics - designing clinical research and biostatistics", organised by the Musculoskeletal Pharmaco-epidemiology group at NDORMS.
Sara is currently supervising four DPhil students and an MSc student, as well as visiting PhD students, and she is interested in supervision opportunities.