My research focuses on developing and applying computer algorithms from the area of optimization, machine learning and reinforcement learning to engineering systems. The applied branch of my research looks at bioprocess control, optimization and scale-up.
I am currently an EPSRC Research Fellow hosted at the Centre for Process Systems Engineering at the Department of Chemical Engineering, Imperial College London.
I will be starting as a Lecturer (Assistant Professor) and head of the Optimisation and Machine Learning for Process Systems Engineering group from April 2020 at the Department of Chemical Engineering, Imperial College London.
I hold a PhD from the Department of Chemical Engineering and Biotechnology at the University of Cambridge, where I received the Danckwerts-Pergamon award for the best PhD dissertation of 2017. I received my undergraduate degree from the National Autonomous University of Mexico (UNAM).
et al., 2019, Comparison of physics-based and data-driven modelling techniques for dynamic optimisation of fed-batch bioprocesses, Biotechnology and Bioengineering, Vol:116, ISSN:0006-3592, Pages:2971-2982
et al., 2019, Hybrid physics-based and data-driven modeling for bioprocess online simulation and optimization, Biotechnology and Bioengineering, Vol:116, ISSN:0006-3592, Pages:2919-2930
et al., 2019, Deep learning-based surrogate modeling and optimization for microalgal biofuel production and photobioreactor design, Aiche Journal, Vol:65, ISSN:0001-1541, Pages:915-923
et al., 2019, Review of advanced physical and data-driven models for dynamic bioprocess simulation: Case study of algae-bacteria consortium wastewater treatment, Biotechnology and Bioengineering, Vol:116, ISSN:0006-3592, Pages:342-353
del Rio-Chanona EA, Zhang D, 2018, A Bilevel Programming Approach to Optimize C-phycocyanin Bio-production under Uncertainty, 10th IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM), ELSEVIER SCIENCE BV, Pages:209-214, ISSN:2405-8963