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
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
- Advanced real-time processing of qEEG signals for event detection in ICUs (on course, Author: Laura López)
- Towards a data-driven methodology for the management of acute out-of-hospital stroke patients (on course, Author: María Ríos)
- New computational approaches based on Artificial Intelligence for the study of neurodegenerative diseases (on course, Author: Fernando García, Co-advised also by: Jordi Matías-Guiu)
- Development of deep learning techniques and strategies in the diagnosis and progression of neurological diseases (on course, Author: Laura Hernández, Co-advised also by: Jordi Matías-Guiu)
- A machine learning perspective on personalized medicine (on course, Author: Carlos Moral, Co-advised also by: Jordi Matías-Guiu)
- Learning Strategies For Knowledge Acquisition from Heterogeneous Data. Application To The Detection Of Cognitive Impairment In Multiple Sclerosis (on course, Author: Ana Cortés, Co-advised also by: Jordi Matías-Guiu)
- Personalized recommendation of therapeutic protocols through automatic design of predictive models from sequential data, and their applications in bioengineering (on course, Author: Luis García, Co-advised also by: José L. Risco)
- Integrated system architecture for Internet of Things model-driven design with applications in medicine (2021, Author: Kevin Henares, Co-advised also by: José L. Risco and Román Hermida)
- Metodologías De Procesamiento De Datos En El Ámbito E-health Para La Categorización De Respuestas Terapéuticas En Pacientes Con Migraña (2020, Author: Franklin Parrales, Co-advised also by: Alberto A. del Barrio)
- Rapid runtime power and performance profiling of large scale applications (2020, Author: Juan Carlos Salinas, Co-advised also by: Marina Zapater and José M. Moya)
- Robust Modeling for Information Acquisition in Biophysical and Critical Scenarios (2018, Author: Josué Pagán, Co-advised also by: José L. Risco and José M. Moya)
- Proactive Power and Thermal Aware Optimizations for Energy-Efficient Cloud Computing (2017, Author: Patricia Arroba, Co-advised also by: Jose M. Moya)
- Diseño y Validación de Políticas de Transmisión de Datos en Redes Inalámbricas de Sensores de Bajo Consumo (2015, Author: Mónica Vallejo, Co-advised also by: Joaquín Recas)
- Proactive and Reactive Thermal Aware Optimization Techniques to Minimize the Environmental Impact of Data Centers (2015, Author: Marina Zapater, Co-advised also by: Jose M. Moya)
- Thermal Aware Design Techniques for Multiprocessor Architectures in Three Dimensions (2013, Author: David Cuesta, Co-advised also by: J. Ignacio Hidalgo and Jose L. Risco)
- Bioinspired heuristics for the thermal-aware Floorplanning of 3D MPSoCs (2013, Author: Ignacio Arnaldo, Co-advised also by: J. Ignacio Hidalgo and Jose L. Risco)
- Analysis and implementation of hardware techniques for low-energy instruction memory organisation in embedded systems (2013, Author: Antonio Artes, Co-advised also by: Francky Catthoor)
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 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.