Nikos Sidiropoulos headshot
NS

Nikolaos D. Sidiropoulos

Professor
Department Chair
Unit: School of Engineering and Applied Science
Department: Department of Electrical and Computer Engineering
Office location and address
C-219 Thornton Hall
351 McCormick Rd
Charlottesville, Virginia 22903
Education
B.S. Aristotle University of Thessaloniki, Greece, 1988
Ph.D. University of Maryland, College Park, 1992
Biography

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).

Blind Carbon Copy on Dirty Paper: Seamless Spectrum Underlay made Practical
Source: U.S. National Science Foundation (NSF)
July 01, 2021 – June 30, 2024
III: Small: A Submodular Framework for Scalable Graph Matching with Performance Guarantees
Source: U.S. National Science Foundation (NSF)
October 01, 2019 – September 30, 2022
III:Medium: High-Performance Factorization Tools for Constrained and Hidden Tensor Models
Source: Regents of the University of Minnesota
September 01, 2017 – August 31, 2022
Geometric Factorization Tools for Community Mining
Source: U.S. DOD - Army - Aro
August 01, 2019 – July 31, 2022
Collaborative Research: Multimodal Sensing and Analytics at Scale: Algorithms and Applications
Source: U.S. National Science Foundation (NSF)
September 01, 2018 – August 31, 2021
Robust and Scalable Volume Minimization-based Matrix Factorization for Sensing and Clustering
Source: U.S. National Science Foundation (NSF)
September 01, 2018 – June 30, 2021
Machine Learning Approaches for Target Spectrum Detection in Hyperspectral Images
Source: Manufacturing Techniques Inc
December 01, 2018 – November 30, 2019
APMA 3100: Probability
Credits: 3
A calculus-based introduction to probability theory and its applications in engineering and applied science. Includes counting techniques, conditional probability, independence, discrete and continuous random variables, probability distribution functions, expected value and variance, joint distributions, covariance, correlation, the Central Limit theorem, the Poisson process, an introduction to statistical inference. Prerequisite: APMA 2120 or equivalent.
ECE 4750: Digital Signal Processing
Credits: 3
An introduction to digital signal processing. Topics include discrete-time signals and systems, application of z-transforms, the discrete-time Fourier transform, sampling, digital filter design, the discrete Fourier transform, the fast Fourier transform, quantization effects and nonlinear filters. Prerequisite: ECE 3750
ECE 4907: Electrical Engineering Projects
Credits: 1–3
Under faculty supervision, students plan a project of at least one semester's duration, conduct the analysis or design and test, and report on the results. If this work is to be the basis for an undergraduate thesis, the course should be taken no later than the seventh semester. Prerequisite: Instructor permission.
CS 6501: Special Topics in Computer Science
Credits: 3
Course content varies by section and is selected to fill timely and special interests and needs of students. See CS 7501 for example topics. May be repeated for credit when topic varies. Prerequisite: Instructor permission.
ECE 6502: Special Topics in Electrical and Computer Engineering
Credits: 1–3
A first-level graduate course covering a topic not normally covered in the graduate course offerings. The topic will usually reflect new developments in the electrical and computer engineering field. Offering is based on student and faculty interests. Prerequisite:  Instructor permission.
ECE 6711: Probability and Stochastic Processes
Credits: 3
Topics include probability spaces (samples spaces, event spaces, probability measures); random variables and vectors (distribution functions, expectation, generating functions); and random sequences and processes; especially specification and classification. Includes detailed discussion of second-order stationary processes and Markov processes; inequalities, convergence, laws of large numbers, central limit theorem, ergodic, theorems; and MS estimation, Linear MS estimation, and the Orthogonality Principle. Prerequisite: APMA 3100, MATH 3100, or equivalent.
ECE 6750: Digital Signal Processing
Credits: 3
A first graduate course in digital signal processing. Topics include discrete-time signals and systems, application of z-transforms, the discrete-time Fourier transform, sampling, digital filter design, the discrete Fourier transform, the fast Fourier transform, quantization effects and nonlinear filters. Additional topics can include signal compression and multi-resolution processing.
ECE 8897: Graduate Teaching Instruction
Credits: 1–12
For master's students.
ECE 9897: Graduate Teaching Instruction
Credits: 1–12
For doctoral students.
ECE 9999: Dissertation
Credits: 1–12
Formal record of student commitment to doctoral research under the guidance of a faculty advisor. May be repeated as necessary.

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, CAMSAP 2015

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