Dr Tabassom Sedighi

Post-Doctoral Research Fellow in Statistical Modelling

Vision and Eye Research Institute

Faculty:Faculty of Health, Education, Medicine and Social Care

School:Medicine

Location: Cambridge

Areas of Expertise: Sustainability , Artificial Intelligence , Machine learning

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.sedighi@aru.ac.uk

Background

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.

Spoken Languages

  • Farsi

Research interests

  • Environmental science
  • Flood-loss estimation
  • Sustainability
  • Biostatistics
  • Statistical modelling
  • Bayesian modelling - Bayesian networks
  • Nonparametric Bayesian modelling
  • Uncertainty quantification
  • Risk analysis
  • Data analysis
  • Supervised and unsupervised machine learning techniques
  • Artificial intelligence (neural network / artificial neural network)
  • Spatial-temporal data analysis
  • Physics
  • Control Engineering
  • Fault detection and prediction
  • No Fault Found
  • Mathematical modelling

Areas of research supervision

Tabassom supervises PhD projects and MSc theses related to her research interests.

Qualifications

  • PhD in Complex Systems Modelling by Use of Machine Learning, School of Aerospace, Transport and Manufacturing, Cranfield University
  • MSc in Control Engineering, Control Theory and Application Centre, Coventry University
  • BSc in Physics, Shahid Chamran University of Ahvaz, Iran

Memberships, editorial boards

  • United Kingdom Automatic Control Council (UKACC)
  • International Federation of Automatic Control (IFAC)
  • Complex Systems Society (CSS)
  • European Geosciences Union (EGU)
  • Associate editor for International Journal of Strategic Engineering (IJoSE)

Selected recent publications

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

Recent presentations and conferences

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.