Namrata Vaswani
Professor of ECE, Iowa State University

(courtesy appointment in Mathematics)
3121 Coover Hall, Ames IA 50011, Email: namrata  AT iastate  DOT edu    Phone: 515-294-4012  

Biography

CV

Publications

Software

Recent Talks

Service

Some Key Papers and Research Summary

Teaching

Students

Funding

 

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).

Publications

Biography:

Namrata Vaswani received a B.Tech. from the Indian Institute of Technology (IIT-Delhi), in 1999 and a Ph.D. from the University of Maryland, College Park, in 2004, both in Electrical Engineering. During 2004-05, she was a postdoc and research scientist at Georgia Tech. Since Fall 2005, she has been with the Iowa State University where she is currently a Professor of Electrical and Computer Engineering. She also holds a courtesy appointment in Mathematics. Her research interests lie at the intersection of data science and machine learning for high dimensional problems, signal and information processing, and computer vision and bio-imaging. Her most recent work has been on provably correct and practically useful algorithms for online dynamic robust PCA and for recursive sparse recovery.

 

Prof. Vaswani has served one term as an Associate Editor for the IEEE Transactions on Signal Processing (2009-2012). She is a recipient of the Harpole-Pentair Assistant Professorship at Iowa State (2008-09), the Iowa State Early Career Engineering Faculty Research Award (2014) and the IEEE Signal Processing Society Best Paper Award (2014) for her Modified-CS paper (IEEE Trans. Sig. Proc. 2010).

 

Google Scholar Profile

 

Full CV

News

 

Research

In the last several years Prof. Vaswani`s work has focused on developing provably accurate online algorithms for various high-dimensional structured data recovery problems such as online robust principal components' analysis (PCA), online matrix completion, or online sparse matrix recovery (recursive recovery of sparse vector sequences) / dynamic compressed sensing. Her group also does work on proof-of-concept applications in dynamic magnetic resonance imaging (MRI) and video analytics. Most recent and ongoing work:

Professional Service:



Graduate Students:

Funding:

Teaching:

Office hours for Fall 2016: Tuesday-Wednesday 2-3pm or by appointment

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