Luca FAES - Research Fellow 

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Full Curriculum vitae 
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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 was a Research Fellow on system identification and modeling at the Medical Biophysics Division of ITC-irst (Institute for Scientific and Technologic Research), Trento, until 2001, and at the Biophysics and Biosignals Laboratory of the Department of Physics, University of Trento, until 2008. He is currently with the Interdepartmental Center for Biotechnologies (BIOtech) of the University of Trento. He has been visiting scientist at the Dept. of Biomedical Engineering, State University of New York, Stony Brook (May-July 2007), and at the Dept. of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA (Sept-Dec 2010).

Luca Faes is a member of the IEEE Enginering in Medicine and Biology Society (IEEE-EMBS), and of the Italian Society of Chaos and Complexity. He is Associate Editor for the Signal Processing Theme (since 2008) and co-chair of the Track on Connectivity and Causality (since 2011) of the IEEE-EMBS Annual International Conference. He is member of the board of the journal ISRN Biomedical Engineering (launched in 2012). He has been Guest Editor of the special issues “Methodological Advances in Brain Connectivity” (Comp. Math. Methods Med. 2012) and “Assessing Causality in Brain Dynamics and Cardiovascular Control” (Phil. Trans. Royal Soc. A 2013).

The research interests of Luca Faes regard digital signal processing and system modeling aimed to the characterization of physiological systems. His research activity is focused on the development of advanced methods for time series analysis and model identification, with application to the study of the physiological mechanisms underlying cardiac atrial fibrillation, cardiovascular control and brain activity and connectivity. Within this field, he has authored three book chapters and about 100 papers in peer-reviewed international journals (see full list) and conference proceedings, receiving more than 550 citations until now.


10 Selected Papers (see full publication list)

  • L Faes, G Nollo, A Porta, 'Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series', Entropy; special issue on “Transfer Entropy”, 2013; 15(1):198-219.
  • L Faes, S Erla, G Nollo: 'Measuring connectivity in linear multivariate processes: definitions, interpretation and practical analysis', Comp Math Methods Med, special issue on “Methodological Advances in Brain Connectivity”, 2012; 140513:18 pages.
  • L Faes, G Nollo, A Porta: 'Information-based detection of nonlinear Granger causality in multivariate processes via a nonuniform embedding technique', Phys Rev E; 2011; 83(5 Pt 1):051112.
  • L Faes, A Porta, G Nollo: 'Testing frequency domain causality in multivariate time series', IEEE Trans Biomed Eng 2010; 57(8):1897-1906.
  • L Faes, Ki H Chon, G Nollo: 'A method for the time-varying nonlinear prediction of complex nonstationary biomedical signals', IEEE Trans Biomed Eng 2009;56(2):205-209.
  • L Faes, G Nollo, K H Chon: 'Assessment of Granger causality by nonlinear model identification: application to short-term cardiovascular variability', Ann Biomed Eng 2008;36(3):381-395.
  • L Faes, L Widesott, M Del Greco, R Antolini, G Nollo: 'Causal cross-spectral analysis of heart rate and blood pressure variability for describing the impairment of the cardiovascular control in neurally mediated syncope', IEEE Trans Biomed Eng 2006;53:65-73.
  • G Nollo, L Faes, A Porta, R Antolini, F Ravelli: 'Exploring directionality in spontaneous heart period and systolic pressure variability interactions in humans. Implications in the evaluation of the baroreflex gain', Am J Physiol Heart Circ Physiol 2005;288(4):H1777-H1785.
  • L Faes, GD Pinna, A Porta, R Maestri, G Nollo: 'Surrogate data analysis for assessing the significance of the coherence function', IEEE Trans Biomed Eng 2004;51(7):1156-1166.
  • L Faes, G Nollo, R Antolini, F Gaita, F Ravelli: 'A method for quantifying atrial fibrillation organization based on wave morphology similarity', IEEE Trans Biomed Eng 2002;49:1504-1513.



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Last updated February 1,2013