School:School of Medicine
Tabassom is an internationally recognised control engineer and Bayesian modeller. She focuses on different aspects of machine learning and statistical techniques for decision making and risk analysis. She has develops Bayesian modelling through her postgraduate and doctoral studies, and now her research career.
Tabassom gained her BSc in Physics and undertook her MSc in Control Engineering (Coventry University, UK). She undertook her PhD under the supervision of Prof. Peter Foote and Prof. Andrew Starr at Cranfield University as part of the No Fault Found (NFF) project sponsored by EPSRC and BAE systems. She was actively involved in the NFF project regarding the intermittent fault detection and prediction of test facilities for assessment of intermittent fault patterns and deployment statistical methods (Dynamic Bayesian Network, Gaussian process, etc.) for intermittent fault prediction.
Tabassom's focus is on different aspects of machine learning and statistical techniques on spatial-temporal data. She had responsibility as Research Fellow for interpreting case studies, collected data, practitioner practices and policies for governance into a Systems Dynamics model capable of handling the requisite variety of cases and developing insights into the evaluation of different policies.
Tabassom supervises PhD projects and MSc theses related to her research interests.
Sedighi, T., Varga, L., Hosseinian-Far, A., Daneshkhah, A., 2021. Economic evaluation of mental health effects of flooding using Bayesian networks. International Journal of Environmental Research and Public Health, 18(14), p. 7467.
Sedighi, T., Varga, L., 2021. Evaluating the Bovine Tuberculosis Eradication Mechanism and Its Risk Factors in England’s Cattle Farms. International Journal of Environmental Research and Public Health, 18(7), p. 3451.
Sedighi, T., Hosseinian-Far, A., Daneshkhah, A., 2021. Measuring local sensitivity in Bayesian inference using a new class of metrics. Communications in Statistics - Theory and Methods. doi: 10.1080/03610926.2021.1977956
Sedighi, T., 2021. Pedometric Webinar held online 16-17 June.
Sedighi, T., 2020. Soil properties prediction using Bayesian methods, 22nd EGU General Assembly, held online 4-8 May.