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 Assistant Professor 

Boise State University Department of Mathematics

mperlmutter@boisestate.edu

I will be an Assistant Professor in the Department of Mathematics at Boise State University.  I am also an affiliate with the Computing PHD program. Here is my google scholar profile and my CV . My current research is focused on the Mathematics of Data Science and Applied Harmonic Analysis. 

More specifically, in recent years my primary area of research have been Geometric Deep Learning. In this field, I work on developing, analyzing, and applying deep learning methods for graph- and manifold-structured data.  This includes both (a) work on the geometric scattering transform, a predesigned, wavelet-based model of neural networks, and (b) work constructing high-performing networks for signed and/or directed graphs. In the past year, I have become increasingly interested in using these methods in biomedical applications such as AI-aided drug discovery, analyzing metabolic networks,  and predicting patient outcomes from single-cell data. 

I have also worked in extensively on phase retrieval problems arising in ptychographic imaging. My work in this field has focused on developing computationally efficient, noise-robust algorithms with provable recovery guarantees for inverse problems arising from structured, locally supported, phaseless measurements. 

 Additionally, I have also worked on problems related to applied probability, audio denoising, data-set benchmarking,  tensor compression, and have recently begun working on on problems related to remote sensing for ecological data as well as data science for hydrology (water-energy systems).

From Fall 2020-Spring 2023, I was a Hedrick Assistant Adjunct Professor in the math department at UCLA working under the supervision of Deanna Needell.  From Fall 2017-Summer 2020, I was a postdoc in the  Department of Computational Mathematics, Science and Engineering at Michigan State University working on problems related to Phase Retrieval and the Mathematics of Deep learning under the supervision of Matt Hirn and Mark Iwen.  From Fall 2016-Summer 2017, I was a postdoc in the Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill, working on problems in high-dimensional probability under the supervision of Amarjit Budhiraja.  I did my graduate work at Purdue University working on problems on the interface of probability and harmonic analysis (martingale methods for studying singular integral operators) under the supervision of Rodrigo Bañuelos.