Laura Balzano is an assistant professor in Electrical Engineering and Computer Science at the University of Michigan. She received a BS from Rice University in Electrical and Computer Engineering, MS from the University of California in Los Angeles in Electrical Engineering, and PhD from the University of Wisconsin in Electrical and Computer Engineering.
Laura's research projects are in statistical signal processing, matrix factorization, and optimization, particularly dealing with large and messy data. She has worked in the areas of online algorithms, non-convex formulations for matrix factorization, compressed sensing and matrix completion, network inference, and sensor networks. Her interests are theoretical, however, my favorite mathematical problems are motivated by fascinating and important engineering problems.
Gitlin, A., B. Tao, L. Balzano, and J. Lipor. 2018. “Improving $K$-Subspaces via Coherence Pursuit.” IEEE Journal of Selected Topics in Signal Processing 12 (6): 1575–88. https://doi.org/10.1109/JSTSP.2018.2869363.
Hong, David, Laura Balzano, and Jeffrey A. Fessler. 2018. “Asymptotic Performance of PCA for High-Dimensional Heteroscedastic Data.” Journal of Multivariate Analysis 167 (September): 435–52. https://doi.org/10.1016/j.jmva.2018.06.002.
Hong, D., R. P. Malinas, J. A. Fessler, and L. Balzano. 2018. “Learning Dictionary-Based Unions of Subspaces for Image Denoising.” In 2018 26th European Signal Processing Conference (EUSIPCO), 1597–1601. https://doi.org/10.23919/EUSIPCO.2018.8553117.
Ledva, G. S., L. Balzano, and J. L. Mathieu. 2018. “Exploring Connections Between a Multiple Model Kalman Filter and Dynamic Fixed Share with Applications to Demand Response.” In 2018 IEEE Conference on Control Technology and Applications (CCTA), 217–23. https://doi.org/10.1109/CCTA.2018.8511493.
Du, Zhe, Laura Balzano, and Necmiye Ozay. 2018. “A Robust Algorithm for Online Switched System Identification.” In IFAC Symposium on System Identification.