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Shuang Li |
Shuang Li is an Assistant Professor in the Department of Electrical and Computer Engineering at Iowa State University. Previously she was a Hedrick Assistant Adjunct Professor in the Department of Mathematics at UCLA working with Professor Deanna Needell. She received her PhD in Electrical Engineering (minor in Computational & Applied Math) from the Colorado School of Mines, where she was fortunate to be advised by Professor Michael B. Wakin and Professor Gongguo Tang. Her research mainly focuses on leveraging the low-dimensional structures such as sparsity, low-rankness, and smoothness existed in high-dimensional data in order to develop optimization-based techniques and provide optimality guarantees for many fundamental problems in signal processing and machine learning. Some of her recent research directions include convex and non-convex optimization, game theory, digital beamforming, and tensor analysis.
I am looking for self-motivated and hardworking students with interests in data science, machine learning, and signal processing. Students with strong mathematical backgrounds are especially encouraged to apply. If you are interested, please contact me with your recent CV and transcripts. I will typically respond within 24 hours if there is a potential fit.
What's New
[Sep. 2025] Our paper ‘‘Landscape analysis of simultaneous blind deconvolution and phase retrieval via structured low-rank tensor recovery’’ was posted on arXiv.
[Aug. 2025] I started serving as Chair of the Joint Chapter (SPS, CAS, COM) under the IEEE Central Iowa Section and look forward to contributing to the professional community.
[Oct. 2024] Co-organized and chaired the special session “Tensor Models for Signal Processing and Machine Learning” at the 58th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA.
[Sep. 2024] Started volunteering for the CyMath program, providing weekly tutoring to support K–12 students in mathematics.
[Aug. 2024] Received an NSF ECCS grant on Scalable, Robust, and Distributed Nonconvex Approaches for Structured Tensor Recovery, joint with Ohio State.
[May 2024] Invited talk for the minisymposium on ‘‘Advances in Low-dimensional Representations in Imaging Science’’ at the SIAM Conference on Imaging Science that will be held in Atlanta, Georgia, US during May 28-31, 2024.
[Mar. 2024] Our special session proposal titled “Tensor Models for Signal Processing and Machine Learning” has been accepted at the 58 th Annual Asilomar Conference on Signals, Systems, and Computers, which will be held in Pacific Grove, California October 27 – October 30.
[Feb. 2024] Our paper ‘‘On a class of greedy sparse recovery algorithms – A high dimensional approach’’ was posted on arXiv.
[Feb. 2024] Invited talk for the Computational and Applied Mathematics Seminar at Iowa State University.
[Jan. 2024] I will be attending The Conference on Parsimony and Learning (CPAL), CPAL 2024, that will be held at the University of Hong Kong during January 3-6, 2024.
[Jan. 2024] Our paper ‘‘Iterative singular tube hard thresholding algorithms for tensor completion’’ was accepted by Inverse Problems and Imaging.
[Nov. 2023] Invited talk for our ECpE Department Seminar at Iowa State University.
[Oct. 2023] I was selected to receive the CPAL Rising Star Award.
[Aug. 2023] I will be attending the third research collaboration workshop, ‘‘Women in Data Science and Mathematics’’, WiSDM 2023, that will be held on the UCLA campus during August 7-11, 2023.
[Aug. 2023] I am excited to be joining the Department of Electrical and Computer Engineering at Iowa State University as an Assistant Professor in August 2023!
[Jul. 2023] Our paper ‘‘Stochastic natural thresholding algorithms’’ was accepted by the 57th Asilomar Conference on Signals, Systems, and Computers.
[Apr. 2023] Our paper ‘‘Iterative singular tube hard thresholding algorithms for tensor completion’’ was posted on arXiv.
[Feb. 2023] Invited talk for the Electrical Engineering Graduate Seminar at California Polytechnic State University.
[Jan. 2023] Our paper ‘‘SP2: A second order stochastic Polyak method’’ was accepted by ICLR 2023.
[Nov. 2022] Invited talk for the Applied Math Seminar at the University of California, Irvine.
[Jul. 2022] Our paper ‘‘SP2: A second order stochastic Polyak method’’ was posted on arXiv.
[Jun. 2022] I was selected to receive an AMS Simons Travel Grant (2022-2024).
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[May. 2022] I was selected as a 2022 DARPA Riser.
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[May. 2022] Our paper ‘‘Landscape correspondence of empirical and population risks in the eigendecomposition problem’’ was accepted by IEEE Transactions on Signal Processing.
[Feb. 2022] Our paper ‘‘Local and global convergence of general Burer-Monteiro tensor optimizations’’ was accepted by The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI).