

PABLO MARTINEZ-LEGAZPI AGUILO
SECRETARIO/A PROG. DOC INTERUNIVERISTARIO MECANICA DE FLUIDOS
PROFESOR TITULAR UNIVERSIDAD
FÍSICA MATEMÁTICA Y DE FLUIDOS
FACULTAD DE CIENCIAS
(+34) 91398-9851
Academic Information
BsC Mechanical Engineer. Universidad Carlos III de Madrid. 2005.
MsC Mathematical Engineering. Universidad Carlos III de Madrid .2007.
PhD Mathematical Engineering. Universidad Carlos III de Madrid 2011.
Academic positions held
Adjunt Professor. Thermal Engineering and Fluid Mechanics Department. Universidad Carlos III de Madrid . 2019 – 2021.
Teaching Assistant. Thermal Engineering and Fluid Mechanics Department. Universidad Carlos III de Madrid . 2007 – 2012.
PhD Scolarship. Thermal Engineering and Fluid Mechanics Department. Universidad Carlos III de Madrid . 2005 – 2007.
Research activity
.My field of research aims to broaden the understanding of cardiac function and cardiovascular diagnostic techniques through the application of fluid mechanics and mathematical modeling tools. This philosophy has allowed us to delve into previously unknown aspects of cardiac physiology and propose new diagnostic tools for cardiovascular disease.
Professional experience
Universidad Carlos III de Madrid. Adjunt Professor. 2019-2021
Consorcio de investigación Biomédica en Red (CIBERCV). Researcher. 2018-2021.
Fundación investigación Biomédica del Hospital Gregorio Marañón. Researcher. 2016-2018.
Instituto de Investigación Sanitaria Gregorio Marañón. Juan de la Cierva Researcher. 2014-2016.
San Diego State University . PostDoctoral Employee . 2014.
University of California San Diego. Postdoctoral Fellow. 2012-2014.
Universidad Carlos III de Madrid. Teaching Assistant. 2007-2012.
Universidad Carlos III de Madrid. PhD Student. 2005-2007.
Universidad Carlos III de Madrid. Assistant in Computational Fluid Mechanics .2004 – 2005.
Universidad Carlos III de Madrid. Assistant in Computater Science. 2003-2005.
Teaching
Asignaturas de Grado:
- 61043101 - TÉCNICAS EXPERIMENTALES III
- 61041094 - FÍSICA COMPUTACIONAL I
- 61044069 - TÉCNICAS EXPERIMENTALES IV
- 61044017 - TRABAJO FIN DE GRADO (FÍSICA)
- 61044052 - FÍSICA DE FLUIDOS
Asignaturas de Master:
- 21153121 - FÍSICA DE FLUIDOS FISIOLÓGICOS
- 21153193 - FUNDAMENTOS FÍSICOS DE LA IMAGEN MÉDICA II
- 21153206 - INSTRUMENTACIÓN BIOMÉDICA
- 21153189 - FUNDAMENTOS FÍSICOS DE LA IMAGEN MÉDICA I
- 21153329 - TRABAJO FIN DE MÁSTER EN FÍSICA MÉDICA
- 21153136 - FÍSICA MATEMÁTICA
- 21153263 - TRATAMIENTO DE SEÑALES

N.º of recognized sections of teacher evaluation
2Research
INVESTIGATION GROUPS
- Medical Physics Research group created with the aim of applying physics to medicine, both in its theoretical and applied aspects. + info
PROYECTOS DE INVESTIGACIÓN
- Artificial Intelligence for Non-invasive Hemodynamics. AI4NHEM Echocardiography is the most used imaging technique in cardiovascular medicine. Despite extensive research during decades, echocardiography is limited to predict accurately critical hemodynamic variables such as pulmonary mean and capillary pressures and cardiac output. Thus, invasive right-heart catheterization is still routinely performed to obtain these measurements. We hypothesize that an appropriately designed and trained deep-learning algorithm will improve the accuracy of current hemodynamic estimations derived from ultrasound. The main objective of this proposal is to settle the bases for a deep neural network for providing clinicians with reliable noninvasive estimators of cardiac hemodynamic data. +info
- Clinical Implications of intraventricular flows in patients with heart failure The overarching aim of this study was to implement, validate and transfer to the clinical practice new post-processing methods of cardiac-imaging flow data, in order to widen the characterization and understanding of cardiac physiology while targeting their clinical application. These methods are based on the measurement and quantification of the blood velocity fields inside healthy and diseased human left ventricles (LV), as well as in the indices derived from them +info
N.º of recognized sections of research activity
2Publications
- PUBLICATIONS IN MAGAZINES Ir a Google Scholar

Other activities
Patents, intellectual property, knowledge transferPatent: Mapping and quantifying shear stress and hemolysis in patients
having lvads. Inventors: L.Rossini; P.Martinez-Legazpi; AM. Khan; R. Yotti; J. Bermejo; J.C. del Alamo. Entity: University of California San Diego/ Hospital General Universitario Gregorio Marañón. Application number: WO2019195783A1. Country: USA. Application Date: 05/04/2018. Date granted:10/10/2019
Patent: Mapping and quantifying blood stasis and thrombus risk in the
Heart. Inventors: L.Rossini; P.Martinez-Legazpi; AM. Khan; R. Yotti; J. Bermejo; J.C. del
Alamo. Entity: University of California San Diego/ Hospital General Universitario Gregorio
Marañón. Application number: EP3379999A1. Country: USA. Application Date: 23/11/2016. Date granted:03/10/2018
Patent: Methods for mapping and quantifying blood stasis and thrombosis
risk in the heart. Inventors: L.Rossini; P.Martinez-Legazpi; AM. Khan; R. Yotti; J. Bermejo; J.C. del Alamo. Entity: University of California San Diego/ Hospital General Universitario Gregorio Marañón. Application number: WO2017091746A1. Country: USA
Application Date: 14/11/2015. Date granted:01/06/2017.
Patent: Methods for mapping and quantifying blood stasis and thrombosis
risk in the heart. Inventors: L.Rossini; P.Martinez-Legazpi; AM. Khan; R. Yotti; J. Bermejo; J.C. del Alamo. Entity: University of California San Diego/ Hospital General Universitario Gregorio Marañón. Application number: US20170150928A1. Country: USA. Application Date: 24/11/2015
Actividades científicas y tecnológicas
Others
Personal Web Page: https://www.dfmf.uned.es/~legazpi.pablo/index.html