معرفی
Nikolaos Sidiropoulos is the Louis T. Rader Professor in the Department of Electrical and Computer Engineering at the University of Virginia, School of Engineering and Applied Science. He has previously held faculty positions at the University of Minnesota and the Technical University of Crete, Greece. His research bridges signal processing, machine learning, and communications, with a strong emphasis on tensor decomposition and optimization.
His research interests include:
- Signal Processing
- Machine Learning
- Wireless Communications
- Optimization
- Tensor Decomposition
- Cyber-Physical Systems
- Data Science
His educational background includes a Diploma in Electrical Engineering from Aristotle University of Thessaloniki (1988), and M.S. and Ph.D. degrees from the University of Maryland, College Park (1990, 1992). His recent publications focus on tensor methods, deep learning integration with clustering, and physical layer multicasting, reflecting a trend toward interdisciplinary methodologies that combine classical signal processing with modern machine learning.
Notable scientific awards include:
- NSF/CAREER Award (1998)
- IEEE SPS Best Paper Awards (2001, 2007, 2011, 2022)
- IEEE SPS Donald G. Fink Overview Paper Award (2022)
- IEEE SPS Claude Shannon–Harry Nyquist Technical Achievement Award (2022)
- EURASIP Technical Achievement Award (2022)
- Distinguished Research Award, University of Virginia (2023)
- Fellow of IEEE (2009) and EURASIP (2014)
- Distinguished Lecturer, IEEE SPS (2008–2009)
- ADC Endowed Chair, University of Minnesota (2015)
- Students have won five best student paper awards at IEEE conferences (SPAWC 2012, ICASSP 2014, CAMSAP 2015, DSW 2019, CAMSAP 2023)
He has advised numerous students and postdoctoral researchers, many of whom have gone on to publish influential work. His research has been supported by the National Science Foundation and other major funding agencies. He leads an active research lab at Thornton A012, University of Virginia, focusing on next-generation signal processing and machine learning algorithms.
