Ph.D. in Mathematics, University of California, Davis, 2005-2009. In her thesis, Deanna developed and analyzed the first strongly polynomial algorithms for Compressed Sensing. Deanna is a Professor of Mathematics at UCLA. She won numerous awards for her work, including Sloan Research Fellowship, NSF CARREER Award, IEEE Best Young Author Paper Award, and 2016 IMA Prize in Mathematics and its Applications.
Ph.D. in Statistics, University of Michigan, 2012-2016. Can was co-advised by Professor Elizaveta Levina and me. Can's thesis was on the analysis of sparse networks. Can is a Professor of Statistics at UC Davis.
Ph.D. in Mathematics, University of Michigan, 2014-2018. Elizaveta (Liza) studied how to repair a random matrix, i.e. improve its behavior by modifying a small fraction of the entries. After visiting UCLA as a postdoctoral fellow, Elizaveta became a faculty at Princeton University in 2021.
Ph.D. in Mathematics, University of Michigan, 2015-2018. Yan Shuo studied how to recover low-dimensional structures from high-dimensional data. He advanced mathematical understanding of phase retrieval and non-gaussian component analysis. Yan Shuo is a postdoctoral fellow at UC Berkeley.
Ph.D. in Mathematics, University of California, Irvine, 2014-2019. Jennifer was co-advised with Prof. Hongkai Zhao. She studied how much independence is needed in the classical limit laws of random matrix theory.
Ph.D. in Mathematics, University of California, Irvine, in progress. Kat is working on new mathematical principles for visualizing high-dimensional data.
Yaniv was an NSF Postdoctoral Fellow and Hildebrandt Assistant Professor in Mathematics at University of Michigan during 2011-2014. Yaniv and I developed the first tractable algorithms for single-bit Compressed Sensing. We then extended this work to logistic regression and non-linear Lasso. Yaniv is now Professor of Mathematics at University of British Columbia.
Beatrice was a Postdoctoral Assistant Professor at University of Michigan during 2014-2017. She is an expert in convex geometry and geometric functional analysis. Beatrice co-authored a book in this area when she was still a graduate student.
Anna is a Visiting Assistant professor at UC Irvine during 2019-2022. She is working on mathematical principles of data visualization, iterative linear solvers, and sparse recovery.
March is a Visiting Assistant professor at UC Irvine during 2021-2022. Together Thomas Strohmer and myself, March is trying to build mathematical foundations for synthetic data and its privacy (for example, here, here, and here). March is part of DeepFoundations team.
M.S. in Financial Mathematics, University of Michigan, 2006-2009. Yuting worked with me on a few problems geometric functional analysis. After graduating from University of Michigan, she continued to Risk Management Solutions.
M.S. in Applied and Interdisciplinary Mathematics, University of Michigan, 2014-2015. Joe worked with me on non-linear inverse regression. After graduating from UM, he continued to the Statistics Ph.D. program at UC Berkeley.
David was my REU student in the Summer 2011. He studied developed the high-dimensional version of the notion of median. He used the multivariate median to develop robust Principal Component Analysis for data.
Albert from Princeton University and Alex from University of Michigan were my REU students in the Summer 2012, co-advised with Dr. Yaniv Plan and me. We studied signal recovery from non-gaussian single-bit measurements. Our results were published in the journal Linear Algebra and Applications.
Matthew and Xinyan were my REU students in 2014, co-advised by Dr. Yaniv Plan and me. We developed a model for blood sugar levels in individuals with Type 1 Diabetes.
Annie is a high school student who is developing new mathematical methods for visualization of high-dimensional data.