Welcome! email: mpasha@vt.edu Google Scholar LinkedIn ResearchGate Github CV

Since July 2024 I have been an Assistant Professor (tenure-track) of Data and High Performance Computational Mathematics in the Department of Mathematics at Virginia Tech (VT). My appointment also includes an affiliation in the CMDA program and the Academy of Data Science.
I held a Research Fellow position at ICERM (Brown University) in Spring 2026.
Before joining VT, I was a National Science Foundation (NSF) Postdoctoral Fellow at the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology (MIT) hosted by Prof. Youssef Marzouk and a National Science Foundation (NSF) Postdoctoral Fellow at Tufts University hosted by Prof. Misha Kilmer.

My research lies at the intersection of inverse problems, tensor methods, uncertainty quantification, and machine learning, with a focus on scalable algorithms for high-dimensional data. I develop computationally efficient, structure-exploiting methods to solve large-scale inverse problems, where the goal is to recover complex parameters from limited, noisy, and indirect observations. These problems arise in modern data-driven settings such as scientific machine learning, spatiotemporal modeling, and large-scale data analysis, where datasets are massive and highly structured. My work leverages low-rank tensor representations to overcome the curse of dimensionality, enabling the recovery of millions of parameters in regimes where classical approaches are infeasible. Overall, I integrate tools from numerical linear algebra, optimization, and statistics to design robust, uncertainty-aware methods that scale to contemporary challenges in data science.

From August 2020 to May 2022, I was a departmental Postdoctoral Scholar at the School of Mathematical and Statistical Sciences at Arizona State University, Tempe, Arizona, USA.
During Fall 2020 I was part of a semester long research program at SAMSI.
Prior to joining ASU, for a semester, I was a Visiting Assistant Professor at John Carroll University in Cleveland, Ohio, USA.
I received a Ph.D. in Applied Mathematics at Kent State University in 2020.

Funding:

Memory-aware Accelerated Solvers for Nonlinear Problems in High Dimensional Imaging Applications (PI), July 2024 - June 2027

Source of funding: National Science Foundation, Amount: $325 000.

27th Conference of the International Linear Algebra Society conference funds for Linear Algebra on the Blue Ridge: Panoramas of Theory and Application (PI), May 2026 - April 2027.

Source of funding: National Science Foundation, Amount: $25 000.

Tensor-Based Methods for Large-Scale and High-Dimensional Dynamic Inverse Problems (PI), June 2022 - July 2024

Source of funding: National Science Foundation, Amount: $150 000.

Mathematical Methods in Data Analysis and Imaging, Co-PI, March 2021, Source of funding: CIMPA School Project Proposal, Amount: $12 000.