Pau Herrero Viñas received the M.Eng. degree in Industrial Engineering in 2001 from University of Girona(Catalonia-Spain) and the Ph.D. degree in 2006 from University of Angers (France) and University of Girona.
After receiving his PhD, Pau moved to Doyle’s Group at the Chemical Engineering Department of University of California Santa Barbara (USA), where he spent one year as a postdoctoral research fellow working on an artificial pancreas project in collaboration with Sansum Diabetes Research Institute (USA).
He then spent the following two years at Hospital de Sant Pau (Catalonia–Spain) working as research fellow for the Biomedical Research Networking center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN) leading different eHealth projects for the prevention of type 2 diabetes and management of type 1 diabetes.
Pau is currently a research fellow within the Centre for Bio-Inspired Technology at the Department of Electrical & Electronic Engineering.
His main research interest lies in the field of diabetes technology and antimicrobial resistance (AMR). In field of diabetes management, he is involved in the development of a Bio-inspired Artificial Pancreas. Another ongoing research he is involved in is on the development of a decision support system for type 1 diabetes management based on Case Based Reasoning (CBR) technology.
His research in the field of AMR consists of developing of a point-of-care decision support system to optimize antimicrobial therapy in intensive and secondary care. This system consists of a mobile app that automatically pulls patient data from hospital servers and uses machine learning techniques to help clinicians to make the right choices for antibiotic therapy from the beginning of the treatment. Such technology is currently being tested at the Imperial College Healthcare NHS Trust.
et al., 2017, A systematic review of clinical decision support systems for antimicrobial management: are we failing to investigate these interventions appropriately?, Clinical Microbiology and Infection, Vol:23, ISSN:1198-743X, Pages:524-532
et al., 2017, Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra- day variability, Computer Methods and Programs in Biomedicine, Vol:146, ISSN:0169-2607, Pages:125-131
et al., 2017, Vancomycin therapy in secondary care; investigating factors that impact therapeutic target attainment, Journal of Infection, Vol:74, ISSN:0163-4453, Pages:320-324
et al., 2017, Atomatic adjustment of Basal insulin infusion rates in type 1 diabetes using run-to-run control and case-based reasoning, Artificial Intelligence in Medicine
, 2017, Abstracts from ATTD 2017 10th International Conference on Advanced Technologies & Treatments for Diabetes Paris, France—February 15–18, 2017, Pages:A-1-A-133, ISSN:1520-9156