Manuel Prieto-Matias

Manuel Prieto-Matias is a Full Professor in the Department of Computer Architecture at UCM. His research interests include areas of parallel computing and computer architecture. Most of his activities have focused on leveraging parallel computing platforms and on complexity-effective micro-architecture design. His current research addresses emerging issues related to heterogeneous systems, memory hierarchy performance and energy-aware computing, with a special emphasis on the interaction between the system software and the underlying architecture. He has co-written numerous articles in journals and for international conferences in the field of parallel computing and computer architecture. He is a member of the ACM and IEEE Computer Society.

Office: FIS-217

Google Scholar Profile: http://scholar.google.es/citations?user=t9t6hOAAAAAJ

DBLP: http://dblp.uni-trier.de/pers/hd/p/Prieto:Manuel

José L. Ayala

Full Professor
(+34) 91 3947601
Office 312, Computer Science Faculty

 

Jose L. Ayala is currently a Full Professor in the Department of Computer Architecture and Automation at the Complutense University of Madrid. He received his MSc and PhD degrees in Telecommunication Engineering from the Technical University of Madrid, Spain, in 2001 and 2005, respectively. He is member of the HiPEAC European Network of Excellence, IEEE, ACM, IFIP 10.5 and the Council of Electronic Design Automation. He is also a European representative in several IEEE initiatives: Brain, Smart Cities, and IoT.

His research interests are in the area of data engineering, mathematical modeling, predictive modeling, and wearable monitoring, in the field of medicine. In that field, he collaborates with several hospitals, clinical units, and research centers, to apply the information and communication technologies to solve problems like automatic diagnosis of neurodegenerative diseases, predict the patient’s response to oncology treatments, develop risk models in cardiovascular diseases, mining genomics data, real-time EEG processing, early stroke detection and prediction of evolution, and many others.

Check my latest publications, and current and latest PhD thesis, to know more about my research. If you are a potential PhD student or collaborator in these topics, contact me.

E-mail: jayala [at] ucm.es

Publications

Find all my publications through the following sites:

Researchgate

Google Scholar

Citation indices
     Citations          2176
     h-index            24
     i10-index         57
PhD Thesis
Master Thesis
  • Aplicación de técnicas de machine learning para la identificación de deterioro cognitivo en pacientes de COVID persistente (2022, Author: Álvaro Martínez)
  • Minado de datos de secuenciación de RNA en tumores renales para la predicción de respuesta al tratamiento antiangiogénico (2022, Author: Sandra Alonso)
  • Aplicación de técnicas de aprendizaje automático a la detección de alteraciones cognitivas en enfermos de Esclerosis Múltiple (2021, Author: Jesús González)
  • Methodology, design and implementation of a machine learning tool for the prediction of the response time of targeted therapies in oncology renal patients (2021, Author: Claudio J. Suriel)
  • Tool for automatic diagnosis of neurodegenerative diseases by machine learning techniques (2020, Author: Fernando García)
  • PET software for the identification of hypometabolic brain regions in dementia (2020, Author: Pedro Bueso-Inchausti)
  • Estrategias de Big Data para la evaluación de la respuesta terapéutica inmunológica en tumores genitourinarios raros. Evaluación de técnicas basadas en aprendizaje supervisado. (2019, Author: Laura Hernández)
  • Estrategias de Big Data para la evaluación de la respuesta terapéutica inmunológica en tumores genitourinarios raros. Evaluación de técnicas basadas en aprendizaje no supervisado. (2019, Author: Paula Nieto)
  • Estrategias de Big Data para la evaluación de la respuesta terapéutica inmunológica en tumores genitourinarios raros. Evaluación de técnicas basadas en metaheurísticas (2019, Author: Daniel Reyes)
  • Despliegue y gestión de plataformas basadas en fog computing en el seno de una ciudad interconectada  (2017, Author: Christian Álvarez Sánchez, Co-advised also by: Jose L. Risco)
  • Predicción de resultados de ataque cerebrovascular mediante el análisis de series temporales fisiológicas (2017, Author: Luis García Terriza, Co-advised also by: Jose L. Risco)
  • Análisis funcional de redes cerebrales a través de nuevos paradigmas computacionales en Spiking Neural Networks (2017, Author: José Pedro Manzano Patrón, Co-advised also by: Olga Santos and Borja Ibáñez)
  • Algorithms for Real-Time Symptomatic Migraine Crisis Prediction (2015, Author: Irene de Orbe)
  • Evolutionary approaches to solve the 3D thermal-aware floorplanning problem using heterogeneous processors (2011, Author: Ignacio Arnaldo,  Co-advised also by: J. Ignacio Hidalgo and Jose L. Risco)
  • Adaptive task-migration policies for thermal optimization in MPSoCs (2009, Author: David Cuesta, Co-advised also by: J. Ignacio Hidalgo)
Collaborations

Guillermo Botella Juan

Guillermo Botella received the M.A. Sc. degree in Physics in 1999, the M.A.Sc. degree in  Electronic Engineering in 2001 and the Ph.D. degree in 2007, all from the University of Granada, Spain. He was a research fellow funded by EU working at the Department of Architecture and Computer Technology, University of Granada, Spain and the Vision Research Laboratory at University College London, UK. After that he joined as Assistant Professor and currently as Associated Professor at the Department of Computer Architecture and Automation of Complutense University of Madrid, Spain. He has been  visiting professor from 2008 to 2012 at the Department of Electrical and Computer  Engineering, Florida State University, Tallahassee, USA. His current research interests include Digital Signal Processing, Image, Audio and Video Processing, IP protection as well as different hardware platforms such as FPGAs, GPGPUs, Multicores, Embedded Systems. He serves regularly as reviewer for several IEEE journals.