Dr Sadia Haider joined the Section of Paediatrics at Imperial in 2016 and is a Post-doctoral Research Associate in Statistical Machine Learning. She obtained her PhD in Statistics from the London School of Economics. The focus of her research was the application of latent variable models to longitudinal data. Her first post-doctoral position was at the Wolfson Institute for Preventive Medicine, where she undertook research on the survival and neonatal morbidity outcomes of babies born extremely preterm using the EPIcure birth cohorts.
She is a collaborator on the Study Team for Early Life Asthma Research (STELAR), and her research at Imperial is centred on implementing and developing machine learning models to understand the progression of asthma and eczema from childhood to adulthood using longitudinal and clinical data from five major birth cohorts. The overarching aims of her research are to investigate whether latent variable models can identify novel subtypes of childhood asthma, whether these subtypes are consistent across cohorts, and to investigate whether unique underlying mechanisms for each subtype can be unravelled by analysing genetic and environmental associates. In addition, she has extensive experience of working with clinicians and researchers to advise on the statistical modelling of their data. She recently trained a team in Buenos Aires to apply machine learning techniques to their data and is training researchers in South Africa to analyse longitudinal data.
She has a keen interest in the academic development and welfare of undergraduate medical students and has experience of personal tutoring. She has been appointed as Academic Tutor to Year 1 MBBS students and is an Academic Mentor for Imperial's Data Spark initiative, where teams of students undertake a data science project for corporate clients. She is an Associate Supervisor to two PhD students in the Department of Medicine and has experience of supervising MSc students to completion. She provides teaching assistance to the MSc Business Analytics course at Imperial College Business School. Furthermore, she is involved in various community outreach activities organised by Imperial.
She is open to considering opportunities for statistical advisory or consulting.
et al., 2020, Association of bacterial load in drinking water and allergic diseases in childhood, Clinical and Experimental Allergy, Vol:50, ISSN:0954-7894, Pages:733-740
et al., 2020, Early-life inhalant allergen exposure, filaggrin genotype and the development of sensitization from infancy to adolescence, Journal of Allergy and Clinical Immunology, Vol:145, ISSN:0091-6749, Pages:993-1001
et al., 2020, Longitudinal trajectories of severe wheeze exacerbations from infancy to school age and their association with early-life risk factors and late asthma outcomes, Clinical and Experimental Allergy, Vol:50, ISSN:0954-7894, Pages:315-324
et al., 2019, Different definitions of atopic dermatitis: Impact on prevalence estimates and associated risk factors, British Journal of Dermatology, Vol:181, ISSN:1365-2133, Pages:1272-1279
et al., 2019, Impact of different definitions of atopic dermatitis on phenotyping the long-term course of the disease, Congress of the European-Academy-of-Allergy-and-Clinical-Immunology (EAACI), WILEY, Pages:29-29, ISSN:0105-4538