Department of Mathematics (0123)
460 McBryde Hall, Virginia Tech
225 Stanger Street
Blacksburg, VA 24061-1026Embedded Files
Mirjeta Pasha, Ph.D.Assistant Professor
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.
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) working with Prof. Youssef Marzouk and a National Science Foundation (NSF) Postdoctoral Fellow at Tufts University working with Prof. Misha Kilmer.
My research interests are on high dimensional (tensor) data analysis, regularization for inverse problems, uncertainty quantification, and machine learning. One of my main research goals is in developing computationally efficient numerical methods to solve large-scale inverse problems. Such problems arise from an extended list of applications in data science and engineering, where from limited observations collected from surface measurements and knowledge of the forward process that maps the unknown parameters onto the data, the goal is to reconstruct the unknown parameters. An example is reconstructing images from X-ray tomography data that can then be used to detect possible anomalies in medical diagnosis. Methods and algorithms that I design target applications that seek to recover millions of parameters from typically massive datasets. Those methods commonly rely on numerical linear algebra, but I also use techniques and tools from statistics, numerical optimization, machine learning, and PDEs.
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, where I worked with Profs. Benjamin Bartelle, Malena Espanol, and Shiwei Lan.
During Fall 2020 I was part of a semester long research program at SAMSI, where I worked on dynamic inverse problems, learning techniques for inverse problems, and randomized TT tensors in the working groups led by Profs. Julianne Chung and Arvind Saibaba.
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 under the supervision of Professor Lothar Reichel, and Dr. Alessandro Buccini and a Master of Science in Applied Mathematics in 2019.
If you are interested in working on a project related to my research areas, send me an email mpasha@vt.edu.
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.
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.
Recent News:
08/2025: Our paper A Nodal Discontinuous Galerkin Method with Low-Rank Velocity Space Representation for the Multi-Scale BGK Model with Andres Galindo-Olarte, Joseph Nakao, Mirjeta Pasha, Jing-Mei Qiu, William Taitano is available on Arxiv.
05/2025: Our paper Priorconditioned Sparsity-Promoting Projection Methods for Deterministic and Bayesian Linear Inverse Problems with Jonathan Lindbloom, Jan Glaubitz, and Youssef Marzouk is available on Arxiv.
01/2025: Our paper Efficient Dynamic Image Reconstruction with motion estimation with Toluwani Okunola, Misha Kilmer, and Melina Freitag is now on Arxiv.
01/2025: Our paper Projected iterated Tikhonov in general form with adaptive choice of the regularization parameter with Alessandro Buccini, Silvia Gazzola, Luke Onisk, and Lothar Reichel is now submitted to Numerical Algorithms.
12/2024: Our paper Krylov Subspace Based FISTA‐Type Methods for Linear Discrete Ill‐Posed Problems with Alessandro Buccini, Fei Chen, and Lothar Reichel is published to Numerical Linear Algebra with Applications.
07/2024: Our paper for the python package TRIPs-Py: Techniques for Regularization of Inverse Problmes in Python is accepted in the Numerical Algorithms Journal.
05/2024: New funding secured from NSF on the collaborative grant DMS 2410699: Memory-aware Accelerated Solvers for Nonlinear Problems in High Dimensional Imaging Applications.
05/2024: Giving a talk at Big Data Inverse Problems Workshop in Edinburgh.
04/2024: I was selected as a READ fellow. With my collaborators we will work on Big Data on Journalism and Communication.
03/2024: Very excited to be on the Editorial Board of Applied Mathematics for Modern Challenges.
02/2024: Our python package TRIPs-Py: Techniques for Regularization of Inverse Problmes in Python has been submitted.
01/2024: New paper on tensor completion: Low BM-rank Tensor Completion.
Selected Past events:
Co-organized with Fioralba Cakoni and Aida Maraj the Summer School "Mathematical Methods in Data Analysis", @University of Tirana, Albania, July 18-30, 2022.
Co-organized with Alessandro Buccini, Marco Donatelli, Giuseppe Rodriguez, and Miodrag Spalevic the conference ``NMLSP 2022: Numerical Methods for Large Scale Problems", Belgrade, June 6th - 10th, 2022.
Co-organized with Alessandro Buccini, Marco Donatelli, Giuseppe Rodriguez, and Miodrag Spalevic the summer school ``Recent Advances in Computational and Learning Methods for Inverse Problems ", on July 11-15, 2022, in Cagliari, Italy.
Co-organized with Emille Lawrence, Malena Espanol, Lauren Rose, Magdalena Luca, and Georgia Benkart the monthly "We Speak: Inspiring Women in Math Speaker Series" in honor of AWM’s 50th Anniversary, 2021.
Co-organized with Biji Wong We Speak! Lightning talks by early-career women mathematicians, September 2021.
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