Distinguished Visiting Assistant Professor in Scientific Computing

Emory University

Tufts University Ph.D. in Mathematics

Haverford College B.S. in Mathematics and Statistics

My CV can be found here.

Multidimensional algebra, numerial linear algebra, machine learning, deep neural networks, optimization

My research focuses primarily on developing deep neural networks (DNNs) for scientific applications. DNNs are remarkably flexbile models, applicable to a wide range of applications, and simultaneously are significantly limited by, e.g., computational resources and the data from which they are derived. In my research, I bring mathematical insight to improve DNN training, to create more reliable DNN models, and to interpret the DNN outputs.

Prior to my DNN work, my research focused on multidimensional (tensor) linear algebra. In high-dimensions, standard linear algebra concepts break down and my work focused on developing and using a matrix-mimetic tensor framework for a variety of applications, including image compression and recognition.