Namrata Vaswani
Professor
of ECE and courtesy Professor of Mathematics, Iowa
State University
3121 Coover Hall, Ames IA 50011, Email: namrata AT iastate
DOT edu Phone: 515-294-4012
This
page and the Publications page are not updated frequently. Please refer to Google
Scholar or ArXiv for copies of my recent work; and/or see my CV (updated more
often).
Biography:
Namrata
Vaswani is a Professor of Electrical
and Computer Engineering, and (by courtesy) of Mathematics, at Iowa State University. She received a Ph.D.
in 2004 from the University
of Maryland, College Park and a B.Tech. from
Indian Institute of
Technology (IIT-Delhi) in India in 1999. Her research interests lie at
the intersection of statistical machine learning
/ data science, computer vision, and signal processing. She is a recipient of the Harpole-Pentair
Assistant Professorship and the Iowa State
Early Career Engineering Faculty Research Award at Iowa State. In 2014, she received the IEEE Signal Processing Society (SPS) Best Paper Award
for
her Modified-CS
work that
was co-authored with her graduate student Lu in the IEEE Transactions on Signal
Processing in 2010.
Prof. Vaswani
recently taught an invited short-course on PCA and Robust PCA for Modern Datasets at
IIIT-Delhi under the Global Initiative
of Academic Networks (GIAN) program of Government of India in December
2017. She recently also gave an invited
talk at the International Conference on Computer
Vision (ICCV) workshop on Robust Subspace Learning. She has given invited seminars at universities around the
world including a department colloquium
at UIUC and a department seminar at CMU.
Vaswani has
served the SPS and IEEE in various capacities. She is an Area
Editor for IEEE
Signal Processing Magazine and has served twice as an Associate Editor for
IEEE Transactions on Signal Processing. She is the Lead Guest Editor for a Proceedings
IEEE Special Issue on Rethinking PCA
for Modern Datasets, and of a Signal Processing Magazine Feature Cluster on Exploiting Structure in High-dimensional Data
Recovery, both of which will appear in
2018. She is also the Chair of the Women
in Signal Processing (WiSP) Committee, a steering
committee member of SPS's Data Science
Initiative, and an elected member of the SPTM and IVMSP Technical Committees.
Research: Vaswani's recent
research has focused on provably correct and practically useful online
(recursive) algorithms for the following two structured (big) data recovery problems: (a) dynamic compressive
sensing (CS) and (b) dynamic robust
principal component analysis (RPCA). Online algorithms are needed for real-time applications, and even for
offline applications, they are typically
faster and need less storage compared to
batch techniques. Most importantly, her work on these problems has shown that
online solutions provide a natural way to exploit temporal dependencies in a dataset, without increasing algorithm complexity;
and that exploiting such dynamics provably
results in either reduced sample complexity (in case of dynamic CS) or improved
outlier tolerance (in case of dynamic RPCA). The
former implies proportionally reduced acquisition
time for applications such as MRI where data is acquired one sample at a time. The latter implies increased
robustness to outliers such as
large-sized or slow changing foreground occlusions in videos. All theoretical claims are backed up by
extensive experimental evaluations for
various video analytics applications and medical imaging applications. Vaswani
is also working on (a) studying PCA in data dependent noise, and (b) low
rank phase retrieval. In the past she has worked
on (c) high-dimensional particle filtering algorithms, and (d) on shape tracking and activity recognition within
computer vision.
News
Research
o Short Courses and Tutorials
o Invited Short-Course
Lecturer for a Global Initiative of Academic
Networks (GIAN) course sponsored by the Government of India at IIIT-Delhi, December
2017
o PCA and Robust PCA for
Modern Datasets: Theory, Algorithms, and Applications
o Tutorial at ICASSP 2017
o Big Data Mining in Large but
Structured Noise
o Editorial Work
o Associate Editor, IEEE
Transactions on Signal Processing, 2009-2013, 2017-present
o Lead Guest Editor, Proceedings IEEE
Special Issue
o Rethinking PCA
for Modern Datasets, 2018 (to appear)
o Lead Guest Editor, Signal Processing
Magazine Feature Cluster
o Exploiting Structure in
High-dimensional Data Recovery, 2018 (to appear)
o Guest Editor, IEEE
Journal of Special Topics in Signal Processing (JSTSP) Special Issue on
o Robust Subspace
Learning and Tracking: Theory, Algorithms, and Applications (Lead Guest Editor:
Thierry Bouwmans), to appear in 2019
o Committee Chair
o Chair, Women
in Signal Processing (WiSP) Committee
(Chair-Elect in 2017), Jan 2018 - present
o Symposium and Workshop Organization (as co-Chair)
o Mini-Symposium
on Compressed Sensing and Matrix Completion (co-organizer: Simon Foucart, TAMU), International Linear Algebra Society (ILAS)
o Symposium on Big Data Analysis
and Challenges in Medical Imaging (Lead organizer: Anubha
Gupta), GlobalSIP 2016
o Workshop
on Robust Subspace Learning and Computer Vision (Lead organizer: Thierry
Bouwmans), ICCV 2015
o Symposium on
Information Processing for Big Data, GlobalSIP, 2014
o Key Committees/Boards
o Member, Membership
Board of IEEE Signal
Processing Society (SPS), Jan 2018- present
o Steering Committee Member, Data
Science Initiative of SPS,
April 2017 - present
o Elected Member of
o SPTM (Signal Processing
Theory and Methods) Technical Committee of SPS, Jan 2016 - Dec 2018
o IVMSP (Image, Video, and
Multimedia Signal Processing) Technical Committee of SPS, Jan 2015 - Dec 2017
o Tutorials Chair for IEEE
Intl. Conf. Image Proc. (ICIP) 2008
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