Ana Mincholé Lapuente

Faculty Member

Biography

Ana Mincholé graduated in Physics from the University of Zaragoza, Spain in 2002. She also obtained an MSc with distinction at Chalmers University of Technology, Gothenburg, Sweden, in the MSc program “Nanoscale Physics and Engineering”. She then started a PhD in Biomedical Engineering at the Communication Technology Group at the University of Zaragoza, Spain supervised by Prof. Pablo Laguna. Her PhD focused on the analysis of the electrocardiographic signal and the development of novel ECG biomarkers for the stratification of arrhythmic risk. During her PhD, she conducted research visits to the Laboratory for Biomedical Computer Systems and Imaging at the University of Ljubljana, Slovenia, with Prof. Franc Jager, and to the Argentinian Institute of Mathematics, CONICET with Dr Pedro Arini and Dr Marcelo Risk. After her PhD and a short postdoc experience in the European preDiCt project at the University of Oxford, she was awarded a Marie Curie Intra-European Fellowship for Career Development and joined Prof. Blanca Rodriguez’ group at the Department of Computer Science at the University of Oxford, UK. After the fellowship, she continued working at the University of Oxford holding the position of Senior Research Associate until 2019. Then, she moved to the University of Zaragoza to join the Multiscale in Mechanical and Biological Engineering group within the European PRIMAGE project where she applied her expertise in multiscale modelling and simulation and high-performance computing to model tumour growth. In 2020, she was awarded a Ramón y Cajal Senior Research Fellowship from the Spanish Ministry of Science and Innovation and joined the Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the University of Zaragoza in 2021.

Her research interests include the development and evaluation of synergistic data-driven approaches where modelling and simulation are used to integrate biomedical data at different scales in the investigation of cardiac pathological conditions. This is in line with her expertise in the combination of computational modelling and simulation of physiological processes, biomedical signal analysis and machine learning techniques to stratify risk either drug-induced or due to pathological conditions.