Advance your academic career, collaborate globally, and expand your network— join now !

José J. Rieta

Share Link

Share

Information

José J. Rieta received M.Eng. degrees in Image and Sound Engineering from the Universidad Politécnica de Madrid, Spain, in 1991, an M.Sc. degree in Telecommunications, and a Ph.D. degree in Biomedical Signal Processing from the Universidad Politécnica de Valencia, Spain, in 1996 and 2003, respectively. He is Full Professor at the Electronic Engineering Department of the Universidad Politécnica de Valencia, becoming a Lecturer in 1994. He has taught several subjects related to Electronic and Biomedical Instrumentation, Analog Systems, Data Conversion Systems, and Control Engineering and has been the author of several academic publications in these areas. In 2006, he founded the Biosignals & Minimally Invasive Technologies (BioMIT.org) research group at the same university, where he is the CEO and responsible for the advanced biomedical signal processing line. His research interests include the application of machine learning, artificial intelligence, and statistical and non-linear signal processing to biomedical signals, especially focused on cardiac signals aimed at developing clinical solutions to study, monitor, and characterize the cardiovascular system and cardiovascular pathologies.

Research Keywords & Expertise

artificial intelligenc...
Biomedical Engineering
Biomedical signal proc...
cardiac arrhythmias
Artificial Inelligence

Short Biography

José J. Rieta received M.Eng. degrees in Image and Sound Engineering from the Universidad Politécnica de Madrid, Spain, in 1991, an M.Sc. degree in Telecommunications, and a Ph.D. degree in Biomedical Signal Processing from the Universidad Politécnica de Valencia, Spain, in 1996 and 2003, respectively. He is Full Professor at the Electronic Engineering Department of the Universidad Politécnica de Valencia, becoming a Lecturer in 1994. He has taught several subjects related to Electronic and Biomedical Instrumentation, Analog Systems, Data Conversion Systems, and Control Engineering and has been the author of several academic publications in these areas. In 2006, he founded the Biosignals & Minimally Invasive Technologies (BioMIT.org) research group at the same university, where he is the CEO and responsible for the advanced biomedical signal processing line. His research interests include the application of machine learning, artificial intelligence, and statistical and non-linear signal processing to biomedical signals, especially focused on cardiac signals aimed at developing clinical solutions to study, monitor, and characterize the cardiovascular system and cardiovascular pathologies.