SPS BISP Webinar: 4 October 2022, presented by Dr. Selin Aviyente
Upcoming SPS-BISP Webinar
Title: Multi-Frequency Functional Connectivity Networks of the Brain
Date: 4 October 2022
Time: 4:00 PM Eastern (New York time)
Duration: Approximately 1 Hour
Presenters: Dr. Selin Aviyente

Abstract:
Biography:
Dr. Selin Aviyente received the B.S. degree with high honors in electrical and electronics engineering from Bogazici University, Istanbul, in 1997. She received the M.S. and Ph.D. degrees, both in electrical engineering: systems, from the University of Michigan, Ann Arbor, in 1999 and 2002, respectively.
She joined the Department of Electrical and Computer Engineering (ECE) at Michigan State University in 2002, where she is currently a Professor. Since 2017, she has also been serving as the Associate Chair for Undergraduate Studies in the ECE department. Her research focuses on statistical and nonstationary signal processing, higher-order data representations, and complex network analysis with applications to neuronal signals. In particular, she has made significant contributions to the theory and application of time-frequency analysis, transform-based sparse-feature extraction and classification, and signal and information processing over networks. Apart from pursuing fundamental research to develop better and more powerful data science tools, she has also worked on using existing tools to define and solve new problems, particularly in the area of brain connectomics. Her most recent work focuses on the study of the dynamic functional networks in the brain using EEG and fMRI. She has authored more than 150 peer-reviewed journal and conference papers.
Dr. Aviyente is the recipient of a 2005 Withrow Teaching Excellence Award and a 2008 NSF CAREER Award. She is currently serving on several technical committees of IEEE Signal Processing Society including the Signal Processing Theory and Methods and Bio-imaging and Signal Processing Technical Committees. She is an Associate Editor for IEEE Open Journal of Signal Processing and Digital Signal Processing.

