Nikos Sidiropoulos earned his Ph.D. in Electrical Engineering from the University of Maryland–College Park, in 1992. He has served on the faculty of the University of Virginia, University of Minnesota, and the Technical University of Crete, Greece, prior to his current appointment as Chair of ECE at UVA. His research interests are in signal processing, communications, optimization, tensor decomposition, and factor analysis, with applications in machine learning and communications. He received the NSF/CAREER award in 1998, the IEEE Signal Processing Society (SPS) Best Paper Award in 2001, 2007, and 2011, served as IEEE SPS Distinguished Lecturer (2008-2009), and currently serves as Vice President – Membership of IEEE SPS. He received the 2010 IEEE Signal Processing Society Meritorious Service Award, and the 2013 Distinguished Alumni Award from the University of Maryland, Dept. of ECE. He is a Fellow of IEEE (2009) and a Fellow of EURASIP (2014).
Education:
B.S. Aristotle University of Thessaloniki, Greece, 1988
Ph.D. University of Maryland, College Park, 1992
Awards:
- NSF/CAREER Award, 1998
- IEEE Signal Processing Society Best Paper Award, 2001, 2007, 2011
- Students received three best student paper awards at IEEE conferences SPAWC 2012, ICASSP 2014, CAMSAP2015
- Distinguished Lecturer of the IEEE Signal Processing Society, 2008-2009
- Fellow, IEEE, for contributions to Signal Processing for Communications, NOV. 2008
- IEEE Signal Processing Society Meritorious Service Award “for dedicated service and leadership in the field of signal processing for communications and networking, 2010
- Distinguished Alumni Award, Electrical and Computer Engineering Department, University of Maryland, College Park, 2013
- Fellow, European Association for Signal Processing (EURASIP), for contributions to tensor decomposition and signal processing for communications, 2014
- Appointed ADC Endowed Chair, University of Minnesota, 2015
- Appointed Vice President, Membership, IEEE Signal Processing Society, 2017
Research Interests:
- Signals, Systems, and Data Science
- Machine Learning
- Communications
- Cyber-Physical Systems
