Sergio Martínez Agüero
Investigador/Técnico
Información general
Presentación
  • Sergio Martínez Agüero received the Degree in Telecommunications Technologies Engineering in 2018 at Rey Juan Carlos University. The Degree Thesis, entitled Automatic learning methods for the analysis and prediction of germ resistance to antibiotics in the ICU, obtained the maximum qualification, outstanding Honorable Mention. The supervisors of this Thesis was Cristina-Soguero Ruiz and Inmaculada Mora-Jiménez, with collaboration with the Chief of the Intensive Care Unit of the University Hospital of Fuenlabrada, doctor Joaquín Álvarez Rodríguez. The material of this Thesis was extended, prompting two conference papers submitted and accepted at the Annual Congress of the Spanish Society of Biomedical Engineering, 2018.

    He is pursuing the University Master Degree in Telecommunication Engineering at Rey Juan Carlos University. He is currently working on his Master's Thesis, entitled Deep learning methods on graphs for the prediction of antimicrobial multi-resistance in ICU, which extends the research line of the Degrees Thesis.   

    He participated and was part of the winning team in a local Machine Learning Datathon organized by Rey Juan Carlos University.  Regarding his training in this line, he has successfully completed the following MOOCs: "Machine Learning" given by Stanford University; "DevOps Essentials" and ¿Deep Learning¿ given by deeplearning.ai. 

    Since 2018, he has got several grants. First, in the Mobile Devices Department of Telefónica Global, where he performed tasks such as laboratory performance tests of several terminals, statistical studies on the telephone network, etc. In January 2019, he joined to the Department of Signal Theory and Communications, Telematics and Computing Systems at Rey Juan Carlos University under a collaboration scholarship program, supervised by Cristina Soguero-Ruiz. During this collaboration grant, he continued his research line on machine learning methods in the field of antimicrobial resistance, delving into more complex techniques of deep learning.  Since March 2019 he has been awarded a contract "Grants for the recruitment of Research Assistants from the Community of Madrid. Call 2018" with reference number "PEJ-2018-AI/TIC-11649" at the Universidad Rey Juan Carlos, supervised by Professor Antonio García Marqués.

    He is currently part of 2 competitive projects funded by the Spanish Government: 
    • New machine learning and visual analytics techniques to characterize risk factors of multi-drug resistant bacteria (AAVis-BMR), PID2019-107768RA-I00. IP: Cristina Soguero-Ruiz 01/06/2020-31/05/2023, funded by the Spanish Government.  
    • Extracción de Conocimiento para Predicción de la Evolución Clínica usando Análisis de Datos (Klynilics). IP: Inmaculada Mora-Jiménez, 30/12/2016-29/12/2020, funded by the Spanish Government. 

    In March 2020, he started to prepare a research stay at the University College of London collaborating with the University College Hospital. However, this stay was suspended due to the COVID-19 situation and the quarantine. 

    For more information about the projects and research line of the researcher please visit the following 
    link.

Méritos
Listado de proyectos (Últimos 10 años)
Códigos de investigador
Publicaciones
  • His starting point in the world of scientific dissemination began in Congreso Anual de la Sociedad Española de Ingeniería Biomédica in 2018 with the following papers: 

    • Estudio de la evolución temporal de la resistencia antimicrobiana de gérmenes en la unidad de cuidados intensivos, Martínez-Agüero, Sergio and Mora-Jiménez, Inmaculada and Lérida-García, Jon and Álvarez-Rodríguez, Joaquín and Soguero-Ruiz, Cristina, Congreso Anual de la Sociedad Española de Ingeniería Biomédica 2018. 
    • Análisis de correspondencias para el estudio de la sensibilidad antibiotica de gérmenes en la UCI, Lérida-García, Jon and Mora-Jiménez, Inmaculada and Martínez-Agüero, Sergio and Álvarez-Rodríguez, Joaquín and Soguero-Ruiz, Cristina, Congreso Anual de la Sociedad Española de Ingeniería Biomédica 2018. 
    Thanks to this paper he was invited to publish an article as a journal extension in June 2019 in the journal entropy (indexed in JCR with a Q2 factor).  This article was chosen as editor choice, the details are shown below: 
    • Machine Learning Techniques to Identify Antimicrobial Resistance in the Intensive Care Unit, Martínez-Agüero, Sergio and Mora-Jiménez, Inmaculada and Lérida-García, Jon and Álvarez-Rodríguez, Joaquín and Soguero-Ruiz, Cristina, Entropy, 2019. 
    In 2020, following the same line of research contributed to the 24th European Congress of Artificial Intelligence, with 3 different articles:  
    • Temporal Feature Selection for Characterizing Antimicrobial Multidrug Resistance in the Intensive Care Unit, Óscar Escudero-Arnanz and Inmaculada Mora-Jiménez and Sergio Martínez-Agüero and Joaquín Álvarez-Rodríguez and Cristina Soguero-Ruiz, SP4HC workshop at 24th European Congress of Artificial Intelligence, 2020. 
    • Modelling Temporal Relationships in Pseudomonas Aeruginosa Antimicrobial Resistance Prediction in Intensive Care Unit, Àlvar Hernàndez-Carnerero and Miquel Sànchez-Marrè and Inmaculada Mora-Jiménez and Cristina Soguero-Ruiz and Sergio Martínez-Agüero and Joaquín Álvarez-Rodríguez, SP4HC workshop at 24th European Congress of Artificial Intelligence, 2020. 
    • Applying LSTM Networks to Predict Multi-drug Resistance Using Binary Multivariate Clinical Sequences, Sergio Martínez-Agüero and Inmaculada Mora-Jiménez and Joaquín Álvarez-Rodríguez and Antonio García Marqués and Cristina Soguero-Ruiz, 24th European Congress of Artificial Intelligence, 2020.