Dr Maryam Parvizi
I am an Assistant Professor at the School of Mathematics, University of Birmingham. My research centers on the development of computational and mathematical models for complex systems in biology, biophysics, and engineering, with particular emphasis on the numerical analysis of partial differential equations, scientific computing, uncertainty quantification, and machine learning.
Previously, I was a Research Fellow in Industrial and Applied Mathematics at the School of Mathematics, University of Birmingham. Before joining UoB, I was an Alexander von Humboldt Fellow and postdoctoral researcher at the Institute of Applied Mathematics, Leibniz University Hannover, under the supervision of Prof. Thomas Wick. I was also a scientific member of the Cluster of Excellence PhoenixD.
Additionally, I was a visiting scholar at the
Mathematical Institute, University of Oxford,
hosted by Prof. Patrick Farrell
Academic Positions
Assistant Professor of Applied Mathematics
Research Fellow in Industrial and Applied Mathematics
Alexander von Humboldt Research Fellow
Institute of Applied Mathematics, Leibniz University Hannover
Postdoctoral Researcher
Institute of Applied Mathematics, Leibniz University Hannover
Visiting Researcher
Institute of Analysis and Scientific Computing, Vienna University of Technology
Education
PhD (Dr. rer. nat.) in Mathematics
Vienna University of Technology
Supervisor: Prof. Jens Markus Melenk
Numerical Methods for PDEs:
Mathematical Biology:
Uncertainty Quantification and Data-Driven Methods:
Research Publications
Published articles:
21- E. Khodadadian, S. Mirsian, S. Shashaani, M. Parvizi, A. Khodadadian, P. Knees, W. Hilber, and C. Heitzinger, A Bayesian inversion supervised learning framework for enzyme activity in graphene field-effect transistors, Machine Learning with Applications, 6, 100718, 2025, DOI: 10.1016/j.mlwa.2025.100718
20- M. Abbaszadeh, M. Parvizi, A. Khodadadian, T. Wick, M. Dehghan, A reproducing kernel particle method (RKPM) algorithm for solving the tropical Pacific Ocean model, Computers & Mathematics with Applications, 179, 197–211, 2025, DOI: 10.1016/j.camwa.2024.12.011
19- M. Abbaszadeh, A. Khodadadian, M. Parvizi, M. Dehghan, D. Xiao, A reduced-order least-squares support vector regression and isogeometric collocation method to simulate the Cahn–Hilliard–Navier–Stokes equation, Journal of Computational Physics, 523, 113650, 2025, DOI: 10.1016/j.jcp.2024.113650
18- S. Mirsian, W. Hilber, E. Khodadadian, M. Parvizi, A. Khodadadian, S. M. Khoshfetrat, C. Heitzinger, B. Jakoby, Graphene-based FETs for advanced biocatalytic profiling: Investigating heme peroxidase activity with machine learning insights, Microchimica Acta, 192, 199, 2025, DOI: 10.1007/s00604-025-06955-y
17- M. Abbaszadeh, A. Khodadadian, M. Parvizi, M. Dehghan, Investigation of a combustion model via the local collocation technique based on moving Taylor polynomial (MTP) approximation/domain decomposition method with error analysis, Engineering Analysis with Boundary Elements, 159, 288–301, 2024, DOI: 10.1016/j.enganabound.2023.11.010
16- S. Shashaani, M. Teshnehlab, A. Khodadadian, M. Parvizi, T. Wick, N. Noii, Using layer-wise training for road semantic segmentation in autonomous cars, IEEE Access, 11, 46320–46329, 2023, DOI: 10.1109/ACCESS.2023.3255988
15- M. Faustmann, J. M. Melenk, M. Parvizi, Caccioppoli-type estimates and 𝓗-matrix approximations to inverses for FEM-BEM couplings, Numerische Mathematik, 150, 849–892, 2022, DOI: 10.1007/s00211-021-01261-0
14- A. Khodadadian, M. Parvizi, M. Teshnehlab, C. Heitzinger, Rational design of field-effect sensors using partial differential equations, Bayesian inversion, and artificial neural networks, Sensors, 22(13), 4785, 2022, DOI: 10.3390/s22134785
13- M. Faustmann, J. M. Melenk, M. Parvizi, 𝓗-matrix approximability of inverses of FEM matrices for the time-harmonic Maxwell equations, Advances in Computational Mathematics, 48, 59, 2022, DOI: 10.1007/s10444-022-09965-z
12- M. Faustmann, J. M. Melenk, M. Parvizi, On the stability of Scott-Zhang type operators and application to multilevel preconditioning in fractional diffusion, ESAIM: Mathematical Modelling and Numerical Analysis (M2AN), 55(2), 595–625, 2021, DOI: 10.1051/m2an/2020079
11- M. Parvizi, A. Khodadadian, M. R. Eslahchi, A mixed finite element method for solving coupled wave equations of Kirchhoff type with nonlinear boundary damping and memory term, Mathematical Methods in the Applied Sciences, 44(17), 12500–12521, 2021, DOI: 10.1002/mma.7556
10- A. Khodadadian, M. Parvizi, C. Heitzinger, An adaptive multilevel Monte Carlo algorithm for the stochastic drift-diffusion-Poisson system, Computer Methods in Applied Mechanics and Engineering, 368, 113163, 2020, DOI: 10.1016/j.cma.2020.113163
9- A. Khodadadian, N. Noii, M. Parvizi, M. Abbaszadeh, T. Wick, C. Heitzinger, A Bayesian estimation method for variational phase-field fracture problems, Computational Mechanics, 66(4), 827–849, 2020, DOI: 10.1007/s00466-020-01876-4
8- M. Parvizi, A. Khodadadian, M. Eslahchi, Analysis of Ciarlet–Raviart mixed finite element methods for solving the damped Boussinesq equation, Journal of Computational and Applied Mathematics, 379, 112818, 2020, DOI: 10.1016/j.cam.2020.112818
7- M. Abbaszadeh, A. Khodadadian, M. Parvizi, M. Dehghan, C. Heitzinger, A direct meshless local collocation method for solving stochastic Cahn–Hilliard–Cook and stochastic Swift–Hohenberg equations, Engineering Analysis with Boundary Elements, 98, 253–264, 2019, DOI: 10.1007/s00466-019-01688-1
6- A. Khodadadian, M. Abbaszadeh, M. Parvizi, M. Dehghan, C. Heitzinger, A multilevel Monte Carlo finite element method for the stochastic Cahn–Hilliard–Cook equation, Computational Mechanics, 64(4), 937–949, 2019, DOI: 10.1007/s00466-019-01688-1
5- M. Parvizi, M. Eslahchi, A numerical method based on extended Raviart–Thomas (ER-T) mixed finite element method for solving the damped Boussinesq equation, Mathematical Methods in the Applied Sciences, 40(16), 5906–5924, 2017, DOI: 10.1002/mma.4442
4- M. Parvizi, M. Eslahchi, The convergence and stability analysis of the Jacobi collocation method for solving nonlinear fractional differential equations with integral boundary conditions, Mathematical Methods in the Applied Sciences, 39(8), 2038–2056, 2016, DOI: 10.1002/mma.3619
3- M. Parvizi, M. Eslahchi, M. Dehghan, Numerical solution of fractional advection–diffusion equation with a nonlinear source term, Numerical Algorithms, 68, 601–629, 2015, DOI: 10.1007/s11075-014-9863-7
2- M. Eslahchi, M. Dehghan, M. Parvizi, Application of the collocation method for solving nonlinear fractional integro-differential equations, Journal of Computational and Applied Mathematics, 257, 105–112, 2014, DOI: 10.1016/j.cam.2013.07.044
1- M. Eslahchi, M. Parvizi, Application of collocation method in finding roots, Iranian Journal of Mathematical Sciences and Informatics, 8, 91–104, 2013, URL: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=311337
Submitted articles:
1- M. Parvizi, A. Khodadadian and T. Wick, Analysis of a fully discretized FDM-FEM scheme for solving thermo-elastic-damage coupled nonlinear PDE systems, submitted for publication, 2024, ArXiv: 2302.01994
Proceedings and talks:
11- M. Parvizi, A Mathematical Energy-Based Framework for Modeling Single-Cell Epithelial Migration, SMB2025, Edmonton, Canada, https://2025.smb.org/MS07/MS-CDEV-06-Part-2.html
10- M. Parvizi, A. Khodadadian, S. Beuchler and T. Wick, Hierarchical LU preconditioning for the time-harmonic Maxwell equations, Domain Decomposition 27, Prague, Czech, January 21-25, 2022, DOI: 10.1007/978-3-031-50769-4_47
9- M. Parvizi, J. M. Melenk and M. Faustmann, \(\mathcal H\)-matrix approximability of inverses of FEM matrices for the time-harmonic Maxwell equations, Domain Decomposition 27, Prague, Czech, July 2022.
8- A. Khodadadian, N. Noii, M. Parvizi and Thomas Wick, A global/local approach for parameter estimation in phase-field fracture problems, ECCOMAS2022, Oslo, Norway, June 2022.
7- M. Parvizi, \(\mathcal H\)-Matrix approximations to inverses for FEM-BEM couplings, GAMM-FA Treffen, Hannover, Germany, June 2022.
6- M. Parvizi, \(\mathcal H\)-Matrix approximations to inverses for FEM-BEM couplings in Maxwell equations, Leibniz meets Humboldt Conference in Optics and Photonics, Hannover, Germany, June 2022. I got travel and accommodation awards for this conference.
5- M. Parvizi, \(\mathcal H\)-Matrix approximations to inverses for FEM-BEM couplings, Chemnitz Finite Element Symposium, Chemniz, Germany, September 2021.
4- A. Khodadadian, N. Noii, M. Parvizi M. Abbaszadeh, T. Wick and C. Heitzinger, Bayesian inversion for variational phase-field fracture problems, Chemnitz Finite Element Symposium, Munich, Germany, March, 2020.
3- M. Faustmann, J. M.Melenk, M. Parvizi and D. Praetorius, Optimal adaptivity and preconditioning for the fractional Laplacian, 90st GAMM Annual Meeting, Vienna, Austria, February 18-22, 2019.
2- A. Khodadadian, M. Parvizi and C. Heitzinger, Optimal multi-level Monte Carlo and adaptive grid refinement for the stochastic drift-diffusion-Poisson system, SIAM Conference on Uncertainty Quantification (UQ 2018), Garden Grove, CA, USA, April 16-19, 2018.
1- M. Faustmann, J. M.Melenk, M. Parvizi and D. Praetorius, Optimal adaptivity and preconditioning for the fractional Laplacian, Sixth Chilean Workshop on Numerical Analysis of Partial Differential Equations (WONAPDE 2019), Conception, Chile, January 21-25, 2019.
Research Grants
1) Alexander von Humboldt Foundation (PI) April 2022 – March 2024
Grant: €100,000
2) UKRI-Analysis for Innovators Round 13 Mini Projects: Stage 2 (Co-PI) Nov 2024 – Feb 2025
Grant: £49,797
3) Royal Society Short Industry Fellowship 2024 (PI) Dec 2024 – May 2025
Project: Mathematical modeling of a new device for tumor measurement
Grant: £22,000
Teaching Experience
Winter Term 2024–25
Winter Term 2023–24
Summer Term 2022–23
Winter Term 2021–22
Summer Term 2020
Winter Term 2015–16
Visiting Positions
Institute of Analysis and Scientific Computing
Vienna University of Technology
hosted by Prof. Jens Markus Melenk
Programming Skills
Languages
Academic Prizes
Alexander von Humboldt Fellowship
Alexander von Humboldt Fellowship, awarded by the Alexander von Humboldt Foundation for two years (2022–2024).
The Best Paper Award 2021
Faculty of Mathematics and Geoinformation, TU Wien, Austria
M. Faustmann, J. M. Melenk and M. Parvizi, On the stability of Scott-Zhang type operators and application to multilevel preconditioning in fractional diffusion. ESAIM: Mathematical Modelling and Numerical Analysis (ESAIM: M2AN), 55(2), 595–625, 2021.