Muhammad Arslan Masood

Project includes the development of an algorithm which can perform tomographical measurements on raw images obtained from ‘X-ray Tomography’. Calculation of the pore size through image processing techniques would lead to the development of ‘Pore network modelling of freeze-drying of porous materials’

Implementation of a velocity mapping function for Phase-Contrast MRI images in Python which paved the way towards Data assimilation in hemodynamic flows – coupling of Phase-Contrast MRI and Computational Fluid Dynamics

Development of artificial neural network and innovative deep learning methods for the prediction and control of process variables in Chemical process engineering with the collaboration of “Fraunhofer-Institut für Fabrikbetrieb und –automatisierung, Magdeburg”

• Computational Fluid Dynamics • Numerical Simulation for Explosion Protection • Simulation of Mechanical Process Engineering • Molecular/ Computational Chemistry and Biology

• Python for Data Science • Probability and Statistics in Data Science Using Python • Machine Learning Tools • Big Data Analytics Using Spark

• Engineering Mathematics • High Performance Fibers • Technical Textiles • Industrial Production Management