I am a Research Assistant Professor at TTIC. Previously, I completed my Ph.D. in Electrical Engineering at Columbia University in 2022, working with John Wright, and my B.S. in Electrical Engineering at the University of Kansas in 2014.

My research interests include the analysis of algorithms for high-dimensional data with low-dimensional structure. I am especially interested in understanding the role of low-dimensional structure in the successes of modern data-driven signal processing frameworks involving deep learning, as a path towards the development of more resource-efficient and reliable models for science and engineering applications.

Recent Updates

• (October 2022) I am co-organizing the third Workshop on Seeking Low-Dimensionality in Deep Neural Networks (SLowDNN). Please consider submitting work (deadline October 30th) and registering to attend!

• (September 2022) I defended my Ph.D. thesis (back in June!), and started as a Research Assistant Professor at TTIC.

• (May 2022) I received the Eli Jury Award from the Columbia EE Department for “outstanding achievement in the area of signal processing”.

• (May 2022) We taught a short course at ICASSP 2022 in May, titled “Low-Dimensional Models for High-Dimensional Data: From Linear to Nonlinear, Convex to Nonconvex, and Shallow to Deep”. Slides are available, and we’ll be making recordings of the lectures available soon!

• (March 2022) New preprint released on invariance-by-design neural architectures for computing with visual data, with theoretical guarantees. Feedback is very much appreciated!

Past Updates