Javier Lorente-Macias

Engineering

Javier Lorente Macías (Marbella, Spain) studied Aerospace Engineering at the Universidad Politécnica de Madrid before completing a Master's degree at Imperial College London. He then joined the University of Cambridge, where his doctoral research focuses on optimal control and inverse modelling of microfluidics in piezoelectric inkjet printheads. These devices are central to high-precision manufacturing applications, ranging from semiconductor fabrication to bioprinting and drug dosing, jetting tens of thousands of droplets per second at precisely controlled positions. A key challenge for the industry is increasing jetting frequency while maintaining droplet reproducibility. However, performance is limited by complex fluid-structure interactions and acoustofluidic phenomena, which are difficult to control and model accurately, and expensive to study experimentally. Javier's work addresses these challenges through physics-based machine learning and numerical optimization. He developed an inverse modelling framework that combines physical modelling with experimental measurements to infer key physical parameters, quantify uncertainty, and reconstruct flow fields that cannot be directly observed experimentally.

In parallel, he developed an optimal control framework for designing piezo-acoustic driving signals that improve jetting performance. Together, these contributions advance both fundamental understanding and practical performance of inkjet microfluidic systems, reducing reliance on trial-and-error design while providing new insight into the physics within piezoelectric inkjet printheads.