Dr Mohammad Saadatfar

Dr Mohammad Saadatfar
Position
Fellow
Department
Department of Applied Mathematics
Qualifications
PhD
Office phone
56361
Email
Skype
mohammad.saadatfar
Office
Cockcroft 4 56

3D image segmentation using machine learning techniques

We aim to use  machine learning techniques to identify minerals and components of three dimensional images obtained from X-ray micro Computed Tomography (XCT).

Dr Mohammad Saadatfar, Dr Shane Latham

Granular materials: understanding their geometry and physics

What is a granular material from geometry and physics perspective? We'll try to understand the fundementals of granular materials in this project.

Dr Mohammad Saadatfar, Dr Nicolas Francois, Dr Vanessa Robins, Prof Timothy Senden

4D structural characterization of carbon-sequestering cements

This project will use high resolution 3D X-ray computed tomography to characterise the evolving structure of reactive magnesium cement materials over months-long time frames, in order to learn how to optimise cement composition and initial structure to enhance CO2 uptake and cement strength, while at the same time minimizing clogging.

Dr Anna Herring, Dr Mohammad Saadatfar, Prof Adrian Sheppard

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