Namrata
Vaswani
Professor of Electrical and Computer Engineering and Anderlik
Professor of Engineering
Courtesy
Professor of Mathematics
Iowa State University
3121 Coover Hall, Ames IA 50011
Phone:
515-294-4012. Email:
firstname@iastate.edu
Always
looking for
1.
Ph.D.
student(s) and or a postdoc
2.
CyMath volunteers: ISU
Math/Stat and Engineering grad students, postdocs, faculty (CyMath is a K-12
Math mentoring/tutoring initiative)
Biography
Namrata Vaswani is a Professor of Electrical
and Computer Engineering, and the Anderlik Professor of Engineering at Iowa State
University. She also holds a courtesy
professorship in the department of Mathematics. 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, and signal processing, and imaging
(MRI and video analytics). Vaswani is also the director of the CyMath
graduate student lead K-8 math mentoring/tutoring program at Iowa State.
She is a recipient
of the Harpole-Pentair Assistant Professorship
(2008-09); the Iowa State Early Career
Engineering Faculty Research Award at Iowa State (2014); the IEEE Signal Processing Society (SPS) Best Paper Award
(2014) for her T-SP paper on Modified-CS co-authored
with her graduate student Lu; the University of Maryland ECE Distinguished Alumni
Award (2019), the Iowa State Mid-Career Achievement in Research Award (2019),
the Anderlik Professorship (July 2019-present).
Vaswani is an AAAS Fellow (class of 2023) and an IEEE Fellow (class of 2019).
Professional
Service and Talks/Tutorials: Prof.
Vaswani 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 has served as an Area Editor for IEEE Signal Processing Magazine, and an
Associate Editor for the IEEE Transactions on Information Theory and the 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.
She served as 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.
Full CV
Graduate Students:
- Alumni
- Zhengyu Chen, Ph.D.,
2022
- Praneeth Narayanamurthy,
Ph.D., 2021, Postdoc at USC
- Seyedehsara (Sara) Nayer, Ph.D., 2021, ASML, USA
- Han Guo, Ph.D., 2019; now at Adobe, USA
- Jinchun Zhan, Ph.D., 2015 (B.S. from USTC,
China), at Google, USA
- Brian Lois, Ph.D., 2015 (co-advised with
Prof Leslie Hogben from the Math dept at ISU), Data Science Manager,
Capital One, Texas, USA; Earlier at AT&T, Dallas.
- Chenlu Qiu, Ph.D., 2013, at Traffic
Management Research Institute (TMRI), China
- Man Basnet, Ph.D., 2013 (co-advised with
Prof. Fritz Keinert from the Math dept at ISU), Lecturer at ISU Mathematics
dept.
- Wei Lu, Ph.D., 2011, Senior Algorithms
Engineer at KLA-Tencor
- Samarjit Das, Ph.D., 2010, R&D Group
Manager at Bosch Research, USA (earlier: postdoc at the Robotics
Institute at CMU)
- MS graduates
- Rituparna Sarkar, M.S., 2012
- Fardad Raisali, M.S., 2012
- Taoran Li, M.S, 2011
- Current Ph.D. students
- Ahmed Ali
Abbasi, started Spring 2023, MS from IT-BHU, Statistics
- Ankit Pratap
Singh, started Fall 2021, MS from Tufts Univ
- Silpa Babu, started Spring 2021,
- Chevonne McInnis, co-advised
with Stephen Holland, AeroE (Engin Mechanics)
- Current M.S. students
- Komal Krishna
Mogilipalepu, started Spring 2023
Funding:
- On Impact of Grade School Math Tutoring by MI-STEM Graduate
Students and Faculty, ISU VPR Office-Community
Vitality RIR, June 2024-May 2025. Co-PI: Mohamed Selim
- CIF:
Small: Efficient and Secure Federated Structure Learning from Bad Data,
NSF-CISE, June 2024 - May 2027. Co-PI: none.
- Fully
Decentralized (Attack-)Resilient Dynamic Low-Rank Matrix Learning,
NSF-Engineering-ECCS, Co-PI, Sept 2022 - Aug 2025. PI: Shana Moothedath
- CIF: Small:
Secure and Fast Federated Low-Rank Recovery from Few Column-wise Linear,
or Quadratic, Projections, NSF - CISE - CCF/CIF, July 2021 - June
2024. Co-PI: Aditya Ramamoorthy
- CIF:
Small: Structured High-dimensional Data Recovery from Phaseless
Measurements, NSF - CISE - CCF, October 2018 - September 2021. Co-PI:
Chinmay Hegde, ECE, Iowa State.
- KLA-Tencor Unrestricted Grant
(Gift), Jan-Dec, 2018 - broadly for research on Outlier Detection via
Dynamic Robust PCA
- CIF: Small:
Online Algorithms for Streaming Structured Big-Data Mining, NSF - CCF
- CIF, 2015-2019
- Distributed
Recursive Robust Estimation: Theory, Algorithms and Applications in Single
and Multi-Camera Computer Vision, NSF - ECCS, 2015-2019. Co-PI: Nicola
Elia, ECE, Iowa State
- Research Grant from Rockwell
Collins and matching funds from Iowa Regents Innovation Fund, 2015-2017.
Co-PI: Soumik Sarkar, Mech Eng, Iowa State
- Co-PI on IDBR Type A - High-Throughput, Large-Scale Plant
Phenotyping Platform, NSF - Division of Biological Infrastructure,
March 2014- Feb 2017, PI: Liang Dong, ECE, Iowa State
- CIF:
Small: Recursive Robust Principal Components Analysis (PCA), NSF
- CCF - CIF, Sept 2011 - Aug 2015. Co-PI: Fritz Keinert, Mathematics, Iowa
State
- RI:
Small: Exploiting Correlated Sparsity Pattern Change in Dynamic Vision
Problems, NSF (IIS - RI), Sept 2011 - Aug 2015.
- Recursive
Reconstruction of Sparse Signal Sequences, NSF - CCF - CIF, July 2009
- June 2012.
- Change Detection in Nonlinear Systems
and Applications in Shape Analysis, NSF - ECCS, August 2007
- July 2010.
- Iowa
State Univ. VPR Office, Faculty Grant Development Award, Summer 2006
Teaching:
- Office Hours:
- Mondays 12-1, Tuesdays 11-12, most Thursday Mornings
- Fall 2024:
- Fall 2024, 2023, 2022, 2021: EE 623: High-Dimensional
Probability and Linear Algebra for Machine Learning
- Primarily based on the
High Dimensional Probability book by R. Vershynin,
and applications of the results in ML.
- Spring 2022: Sabbatical
(FPDA)
- Spring 2024, 2023, 2021,
2020, 2019: EE 425:
Machine Learning: A Signal Processing Perspective
- Spring 2021: EE 322 (Probabilistic Methods for Electrical
Engineers)
- Fall 2020: EE 322 (Probabilistic Methods for Electrical
Engineers)
- Spring 2020: EE 425X:
Machine Learning: A Signal Processing Perspective
- Fall 2019: EE 520 (Special
topics in CSP: Foundations of Statistical ML)
- Spring 2019: EE 425X:
Machine Learning: A Signal Processing Perspective
- Fall 2018: EE 322 (Probabilistic Methods for Electrical
Engineers)