Professor Kazem Rahimi is Professor of Cardiovascular Medicine and Population Health at the University of Oxford, with research interests in hypertension, heart failure, multimorbidity and their risk management, using various big data and digital health methodologies.
Professor of Translational Neuroscience at Oxford University and has research interests in the regulation of tau phosphorylation, in the search for genetic and other biomarkers of Alzheimer’s disease.
Professor of Biomedical Engineering and head of the Analysis Group at The Oxford University Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB).
Professor of Engineering Science at the University of Oxford, UK where he has been co-director of the Visual Geometry Group (VGG), one of the internationally-leading groups in computer vision, since 2012.
Reza is a Biomedical Informatics scientist, whose research interests lie in applying Machine Learning and Big Data technologies to develop novel solutions that can stratify health risks and improve the quality of clinical decision-making.
Dexter is an epidemiologist, who has research interests in the aetiology of vascular disease and determinants of major causes of morbidity and mortality in the population.
Debbie is a clinical trial manager with more than 20 years of clinical research experience working in various roles both in the Pharmaceutical Industry and academia. Debbie joined the Deep Medicine team initially in 2016 to work on the Support-HF2 study and is currently trial manager for the ATEMPT Clinical Trial.
Rema is a senior statistician at the National Perinatal Epidemiology Unit, Nuffield Department of Population Health. She also contributes to the ATEMPT clinical trial. She is passionate about studying exposures and outcomes in reproductive, perinatal, and lifecourse epidemiology. She has an interest in causal inference and the use of advanced statistical methods to address relevant questions.
Abdelaali is a machine learning scientist with interests in extracting actionable insights from big data. His research currently focuses on understanding disease trajectories, multimorbidity patterns and their evolution over time.
Mo specialises in the applications of machine learning on large-scale electronic health records to extract new insights and develop models for prognostication and diagnostication. He is involved in the PEAK Urban and Informal Cities programmes where he focuses on the effects of environmental and sociodemographic factors on health outcomes.
Tom works in the Informal Cities programme where he is using machine learning techniques to predict health outcomes in slums and informal settlements.
Gosia is a consultant cardiologist with expertise in heart diseases associated with diabetes and a member of the NICE Diabetes Pharma committee developing national guidelines for the management of diabetes. Her research experience spans from molecular biology and drug development projects to randomised controlled trials. Her interests focus on cardiovascular complications of diabetes, insulin resistance, and the prediction of heart failure in diabetes patients.
Jeannette is a Clinical Research Fellow in the Deep Medicine Programme who investigates the management of high blood pressure in older patients with underlying chronic health conditions and seeks new approaches to conducting clinical trials in remote settings. She has a keen interest in public health research, clinical trials and evidence-based health care practices.
Emma is part of the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC) research group, she is also investigating the effect of antihypertensive drugs on cancer.
Zeinab is an epidemiologist. Her research focuses on aetiology of cardiovascular diseases and hypertension using methodologies, such as systematic-review and meta-analysis, individual-patient data meta-analysis and genetic epidemiology.
Yunzhe is a geospatial statistician. His research focuses on applications of multisource spatiotemporal data in public health. He is a member of an interdisciplinary research team being led by Professor Kazem Rahimi, and participates in several programmes within Deep Medicine, including the Informal Cities and the PEAK Urban.
Jing is an environmental epidemiologist. Her research interests focus on the health effects of environmental factors including air pollution, traffic noise and greenness in the population, and harnessing epidemiological evidence to better inform policy-making towards healthy built environment.
Milad is an Epidemiologist, who has research interests in blood pressure, cardiovascular disease, and genetic epidemiology. His current research projects involve assessing causal risk factors of valvular heart disease, venous thromboembolism and atrial fibrillation using a combination of large-scale electronic health records and genetic techniques including Mendelian randomisation.
Shishir is a DPhil student with interests in developing machine learning methods for causal inference and representation learning to investigate cardiovascular health.
Yikuan is a DPhil student with interests in Bayesian deep learning, interpretable machine learning, and multimodal representation learning, He's research focuses on investigating deep learning framework for uncertainty estimation and risk factor analysis for cardiovascular disease.
Rachel is a DPhil student in the Nuffield Department of Women’s and Reproductive Health supervised by Dr. Kazem Rahimi. Her research and professional interests focus on reaching vulnerable and hard-to-reach populations with health services. Rachel's DPhil research will improve methods for digital research in informal settlements and study how the inclusion of hard-to-research population can improve health equity.
Ivan is a software architect and engineer. He has been developing scientific software solutions for the last decade.
Wendy has more than 25 years experience working in various Regulatory Affairs roles in the Pharmaceutical Industry supporting drug development projects. Wendy joined the team as Information Governance and Quality Assurance Officer for the ATEMPT Clinical Trial.
Samuel is an environmental epidemiologist with research interests in the health effects of multiple environmental stressors and their potential modifiers, climate change, exposure assessment, respiratory epidemiology, and harnessing data science to better inform environmental health policy-making. He is a researcher of the PEAK-Urban programme and co-leading Informal Cities Health Programme.
Abel was the head of Information Technology and Software Engineering at the Deep Medicine programme. Abel has an extensive experience on managing innovation projects.
Harry is a GIS specialist, developer and data scientist, working in particular on the Informal Cities programme.
Daniel is a professional graphic designer that specialises in project solutions relating to all aspects of web design and development.
Andy was an urban health researcher and Co-founder of the Healthy Cities Network, a global nexus of innovators dedicated to sharing cutting-edge information on urban health.
Yajie's research focused on exploring the complex relationships between health and environment to build an environmental human disease network.
Mariagrazia was a Statistical Programmer/Data Analyst at the Deep Medicine research group.
Roberto was a machine learning scientist. His research focuses on data mining and machine learning for environmental systems modelling and analysis.
Hamid Mohseni has a substantial experience in statistics and biomedical data analysis, including continuous, periodic and categorical data.
Fatemeh was a data scientist with a wide interest in big data mining algorithms and techniques, including machine learning, deep learning and network/graph algorithms.
Amir was a machine learning scientist with interests on data intensive computing platforms, mining massive datasets and deep learning.
Jeff's project focuses on investigating the associations between maternal infection and the risk of childhood leukaemia.
Nathalie was a DPhil student, and her research focusses on the epidemiology of cardiovascular diseases using large real-world data sets, as well as the design of digital health systems for patients with heart failure.
Ana-Catarina was a DPhil student working on blood pressure management in complex populations, namely atrial fibrillation, heart failure and multimorbidity.
Jenny was a medical doctor completing research on chronic comorbid conditions and cardiovascular risk as a Rhodes Scholar. She has a particular interest in non-communicable diseases and intensive care medicine.
Francesca was a machine learning scientist with interests in multi-way processing for sensor arrays through tensor Decompositions.