Areas of expertise

  • Applied Informatics
  • Computational Fluid Dynamics
  • Computing, Simulation & Modelling
  • Environment and Health
  • Safety, Resilience, Risk & Reliability
  • Soil
  • Sustainable Manufacturing
  • Systems Engineering
  • Throughlife Engineering Services

Background

Tabassom Sedighi gained her BSc in Physics and undertook her MSc in Control Engineering (Coventry University, UK). Her primary research interests span in Physics, Control Engineering, mathematical modelling, adaptive controller design, nonlinear observer design, fault detection and isolation, error stability analysis, solving differential equations and Lyapunov equations, data analysis, risk analysis and predicting residual useful life. She had 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 has been actively involved in the NFF project regarding 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.

After her PhD she had the responsibility as a research fellow for interpreting case studies, collected data, practitioner practices and policies for governance, into a Systems Dynamics  (SD) model capable of handling the requisite variety of cases and developing insights into the evaluation of different policies. She was also working with the CECAN team to understand how this SD tool fits into the landscape of methods for complexity evaluation. She was disseminating findings and helping to develop capacity in policymakers and related stakeholders by supporting their use of the SD tool.


Research opportunities

I am interested in the following areas:

Statistics and Machine Learning techniques ( Bayesian methods), working with large volume of data, modelling and simulation complex systems using machine learning techniques with applications in complex engineering,  social, industrial and environmental systems;  infectious disease modelling; decision making and risk analysis; prediction; pattern recognition; fault and degradation detection.

Modelling inter-dependencies between system components using Bayesian models with application in optimised decision making, and system reliability evaluation; system forecasting; uncertainty Quantification/propagation using Gaussian Process emulators;  Optimized decision making under uncertainty and the  Game theory.

Control theory and its applications.


Current activities

I am an internationally recognised control engineer and Bayesian modeller. Focus on different aspects of machine learning and statistical techniques to predict national soil properties. Developing Bayesian modelling through postgraduate, doctoral and researching. Member of United Kingdom Automatic Control Council (UKACC), Member of International Federation of Automatic Control (IFAC), Member of Complex Systems Society (CSS), Associate Editor for International Journal of Strategic Engineering (IJoSE). 



Clients

BAE Systems; DEFRA; Environment Agency.

Publications

Articles In Journals

Conference Papers

Books