This project aims to estimate risks for a range of health conditions based on environmental factors, which can be useful for policy makers even in areas where local health data might be limited.
Mohammad is a Machine Learning Scientist at the University of Oxford. As a member of the interdisciplinary research group Deep Medicine, led by Prof Kazem Rahimi, 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.
Before joining the University of Oxford, he was a postdoctoral researcher at City, University of London focusing on the analysis of high-dimensional optical spectra and bio-signals, and a research assistant at University of Southampton focusing on urban mobility.
Mo's educational background is in Applied Mathematics-Systems and Modelling (PhD, City, University of London), and Electrical Engineering (MSc, City, University of London & BSc, Iran University of Science and Technology).