Biochemical Engineering


Dr Sofia Simaria


Dr Sofia Simaria
  • Post-Doctoral Research Associate, Dep. Biochemical Engineering, University College London, UK (2008-2012) 
  • Honorary Lecturer, Dep. Biochemical Engineering, University College London, UK (2010-2011)
  • Assistant Professor, Dep. Economics, Management and Industrial Engineering, University of Aveiro, Portugal (2006-2008)
  • Teaching Assistant, Dep. Economics, Management and Industrial Engineering, University of Aveiro, Portugal (2002-2006)

Dr Sofia Simaria


  • Lecturer
    Dept of Biochemical Engineering
    Faculty of Engineering Science

Joined UCL


Sofia’s current research focuses on the development of computer-based decision-support models that capture the process-business interface of biopharmaceutical manufacture. She works in the Decisional Tools research group lead by Dr. Suzanne Farid.
Sofia has extensive experience in the development of simulation models and optimisation algorithms for improving the efficiency of assembly line production systems and since she has joined UCL she is bringing that experience into the biopharmaceutical production area. 
As part of the research team of the Centre she contributes to the development of a decision-support optimisation software tool for the bioprocessing sector that can locate the most cost-effective combination of process parameters, process sequence, formulation method and facility design under uncertainty.
She also collaborates on a TSB Technology Programme which is enabling research into decision-support tools that help devise successful business models for novel regenerative medicine therapies such as stem cells and cell-based vaccine cancer therapy.

Award year Qualification Institution
2006 PhD
Doctor of Philosophy
Industrial Studies
Universidade de Aveiro
2001 MAST
Management Techniques
Universidade de Aveiro
1998 LCT
Industrial Engineering
Universidade de Aveiro

Teaching and Training Activities


Sofia coordinates the new MEng/MSc  course module Bioprocess Systems Engineering, designed to provide students with skills in advanced modelling, optimisation and statistical techniques such that they are adequately equipped to address problems related to evaluating the cost-effectiveness and robustness of alternative bioprocess design strategies