Imperial College London

Dr Pau Herrero

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Research Fellow
 
 
 
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Contact

 

p.herrero-vinias

 
 
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Location

 

B422Bessemer BuildingSouth Kensington Campus

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Summary

 

Summary

Pau Herrero currently holds the position of Research Fellow in Biomedical Control Systems at Imperial College London within the Department of Electrical and Electronic Engineering. He is research co-director of the Metabolic Technology Laboratory in the Centre for Bio-Inspired Technology, a multi-disciplinary group that aims to tackle pressing healthcare problems through the utilisation of engineering and data science solutions, with a particular emphasis on transferring these technologies to society.

His research is focused on developing automated drug delivery systems and decision support systems to address open problems in the fields of diabetes and infectious diseases management. He has been Principal Investigator of an H2020 project aiming at developing a diabetes self-management system, which has received the category of 'Tech Ready' by the European Commission's Innovation Radar.

Dr. Herrero graduated with a 1st Class Honours in Industrial Engineering in 2001 from University of Girona and obtained a double-degree Ph.D. on Automation and Applied Informatics in 2007 from Université Angers and University of Girona (Cum Laude). He also spent one year as a postdoctoral researcher at The Doyle Group (University of California Santa Barbara).

He is a member of the Centre for Antimicrobial Optimisation, which aims to optimising antimicrobial use to address the global challenge of antimicrobial resistance. He also serves on the United Kingdom Interval Methods Working Group technical committee, a working group aiming to bring together researchers from UK and abroad working on set-membership methods.

Publications

Journals

Contreras I, Calm R, Sainz MA, et al., 2021, Combining grammatical evolution with modal interval analysis: An application to solve problems with uncertainty, Mathematics, Vol:9

Avari P, Leal Y, Herrero Vinas P, et al., 2021, Safety and feasibility of the PEPPER adaptive bolus advisor and safety system; a randomized control study, Diabetes Technology and Therapeutics, Vol:23, ISSN:1520-9156, Pages:175-186

Zhu T, Li K, Herrero P, et al., 2020, Deep Learning for Diabetes: A Systematic Review., Ieee J Biomed Health Inform, Vol:PP

Moscardo V, Herrero P, Reddy M, et al., 2020, Assessment of Glucose Control Metrics by Discriminant Ratio, Diabetes Technology & Therapeutics, Vol:22, ISSN:1520-9156, Pages:719-726

Zhu T, Li K, Chen J, et al., 2020, Dilated Recurrent Neural Networks for Glucose Forecasting in Type 1 Diabetes, Journal of Healthcare Informatics Research, Vol:4, Pages:308-324

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