WORKSHOP on Signal Processing and Data Analysis


FCUP, Rooms 0.07, 1.19

Date and time: 

October 13, 2017

Information Theory for the Analysis of Physiological Time Series 

Luca Faes, PhD, Research Fellow BIOtech, University of Trento, Italy (,

Part I – Seminar - Scientific framework: 9-11 am, FCUP, FC1 Room 0.07
Part II – Hands-on application: 11-13 am, FCUP, FC1 Room 1.19

General Description: This workshop will introduce interested students and faculty members to the mathematical framework of Information Dynamics, guiding them to the theoretical development of information-theoretic measures descriptive of networks of multiple interacting stochastic processes, to the algorithms for the practical estimation of these measures from time series data, and to their application for the study of the human physiological network probed in healthy and diseased conditions.

Short Bio: Luca Faes received the MS degree in Electronic Engineering from the University of Padova, Italy, in 1998, and the PhD degree in Electronic Devices from the University of Trento, Italy, in 2003. He has been research fellow at the Department of Physics (2003-2008) and at the BIOtech Center (2009-2013) of the University of Trento, and senior researcher at the Bruno Kessler Foundation (Trento, 2014-2017). He has been visiting researcher at the University of Gent (Belgium), the Federal University of Minas Gerais (Brazil), and the State University of New York, Worcester Polytechnic Institute and Boston University (US). Dr. Faes is a member of the IEEE Engineering in Medicine and Biology Society, the European Study Group on Cardiovascular Oscillations (ESGCO) and of the Program Committee of several conferences on medical signal processing. His research interests regard the development of methods for time series analysis and system modeling, with application to cardiovascular neuroscience, cardiac arrhythmias, brain connectivity and network physiology. Within these fields, he authored five book chapters and more than 100 journal publications, receiving more than 2300 citations (h-index 28).