Estefania Lopez-Quiroga

Colleges, School and Institutes


Estefania Lopez-Quiroga has a multidisciplinary background, with a MEng Mining in Engineering and a MSc in Mathematical Engineering and Numerical Simulation.

In 2009, Estefania joined the (Bio)Process Engineering Group (IIM - CSIC) as a PhD candidate fully funded by the Spanish Government (FPI scholarship). Her research there was linked to the FP7 EU project CAFE (Computer-Aided Food Engineering), which gave her the opportunity to spend part of her PhD as visiting student at the University of Manchester (School of Chemical Eng. and Analytical Sciences). She completed her thesis in 2014, receiving a Europaeus PhD (Cum Laude).

Also in 2014, Estefania was appointed as a Postdoctoral Research Fellow at the School of Chemical Engineering (University of Birmingham). Her post was first associated to the EPSRC Centre for the Sustainable Energy Use in Food Chains (CSEF), joining in 2019 the EPSRC Centre for Doctoral Training in Formulation Engineering.

 Since November 2020, Estefania is a Lecturer at the School of Chemical Engineering, a position that is also associated to the EPSRC CDT in Formulation Engineering.


Research interests

Estefania’s research vision is to enable model-based, multiscale yet agile, digital tools that support the shift towards Industry 4.0 methods in Formulation Engineering applications.

She focuses on the integration of formulation engineering methods with mathematical and computational tools to characterise, control and optimise the manufacturing and performance of formulated and/or structured products (foods, pharmaceuticals, FMCG) and chains.

Her current research activities look at:

  • the application of soft matter physics to the modelling of structuring processes: soft matter concepts provide a theoretical framework for the identification of relations between (micro)structure, product function and underlying physic phenomena, so they present potential in formulation engineering applications.
  • the use of reduced order methods to reduce the dimensionality and computational burden of small scale, physics-based models describing structuring processes, like for example crystallisation.
  • the development of semi-empirical and data-driven models to characterise the performance of formulated and structured products and estimate key processing/engineering parameters.
  • the coupling of product and process/plant scale using hybrid models.


Willingness to take PhD students


PhD projects

I4.0 and Formulation Engineering themes