“Science is a wonderful thing if one does not have to earn one’s living at it.” (Albert Einstein)
Jordi Vilà-Valls received the M.Sc. degree in Electrical Engineering from both Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, and Grenoble Institute of Technology (Grenoble INP), Grenoble, France, in 2006. In October 2006, he joined GIPSA-Lab at the Grenoble INP as a Research Assistant with a French Ministry of Science Ph.D. grant. His thesis, entitled “Nonlinear Dynamic Channel Estimation for Mobile Satellite Receivers”, focused on nonlinear Bayesian estimation methods and its applications to synchronization problems for both communications and positioning systems. In 2009, he was a Visiting Researcher at Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), granted with a Short Term Scientific Mission for the project “New Nonlinear Filtering Methods for Synchronization and Bayesian Bounds for Galileo type Signals”. He received the Ph.D. degree in Electrical Engineering (Signal Processing) from Grenoble INP in March 2010.
From October 2010 to October 2012, he was a Postdoctoral Research Associate in the Signal Processing and Communications (SPCOM) group, UPC; and from October 2012 to October 2013 with the Signal Processing for Communications and Navigation (SPCOMNAV) group, Universitat Autònoma de Barcelona (UAB). From February 2014 to April 2015 he was a Research Associate at the Statistical Inference Department, CTTC. From May 2015 to December 2016 he was a Visiting Researcher at the Micro and Nanotechnologies research group (MNT), UPC. Since January 2017 he is back to the Statistical Inference Department at CTTC.
He worked during the last 10 years in several aspects related to advanced statistical signal processing techniques for communications, navigation and tracking systems, with special emphasis on Bayesian inference and adaptive/robust filtering techniques. He has also been a key personnel in several projects funded by the European Commission (EC) and the European Space Agency (ESA). His primary areas of interest include statistical signal processing, estimation and detection theory, nonlinear Bayesian inference, robustness and adaptive methods; with applications to positioning, localization and tracking systems, wireless communications and aerospace science.
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