Research profile

My current research is broadly on theory and numerical methods for inverse problems and uncertainty quantification. In my work, I utilize theories and methods from numerical analysis, PDE theory, probability and statistics, inverse problems, and optimization. My specific areas of interest include (i) Large-scale statistical inverse problems governed by PDEs with infinite-dimensional parameters. A major theme in my research in this area has been theory and numerical methods for optimal design of infinite-dimensional inverse problems governed by PDEs. (ii) Optimization under uncertainty and optimal control of systems governed by PDEs with random coefficient functions. (iii) Global sensitivity analysis for stochastic and time-dependent systems, as well as complex physics systems with high-dimensional inputs and outputs. A common theme in my research has been working on challenging application-driven problems. Some of the application areas featured in my research include porous medium flow, bio-transport in tissues, stochastic chemical kinetics, and epidemiology.

Here you can find a list of my publications, including my peer-reviewed research articles, technical reports, conference proceedings, and abstracts. Below you can also find my technical notes, which I have written over the years as I entered new areas of research or just followed my own curiosity in various areas.

% Slides from the First Year Seminar, October 2020 %[ link ]


    Peer-reviewed journal articles

  1. Isaac Sunseri, Alen Alexanderian, Joseph Hart, Bart van Bloemen Waanders. Hyper-differential sensitivity analysis for nonlinear Bayesian inverse problems. In review. 2022. [ preprint ]
  2. John Darges, Alen Alexanderian, Pierre Gremaud. Extreme learning machines for variance-based global sensitivity analysis. In review. 2022. [ preprint ]
  3. Ethan Dudley, Arvind Saibaba, and Alen Alexanderian. Monte carlo estimators for the Schatten p-norm of symmetric positive semidefinite matrices. Electronic Transactions on Numerical Analysis, 55:213-241. 2022. [ preprint ]
  4. R.D. White, A. Alexanderian, O. Yousefian, Y. Karbalaeisadegh, A. Kasali, H.T. Banks, M. Talmant, Q. Grimal, Marie Muller, and K. Bekele-Maxwell. Using Ultrasonic Attenuation in Cortical Bone to Infer Distributions on Pore Size. In revision. 2021.
  5. Mason Stevens, Isaac Sunseri, Alen Alexanderian. Hyper-differential sensitivity analysis for inverse problems governed by ODEs with application to COVID–19 modeling. In review. 2021.
  6. Michael Merritt, Alen Alexanderian, and Pierre Gremaud. Global sensitivity analysis of rare event probabilities. In review. 2021. [ preprint ]
  7. Helen Cleaves, Alen Alexanderian, and Bilal Saad. Structure exploiting methods for fast uncertainty quantification in multiphase flow through heterogeneous media. Computational Geosciences, 25(6):2167--2189. 2021. [ preprint ]
  8. Alen Alexanderian, Noemi Petra, Georg Stadler, and Isaac Sunseri. Optimal design of large-scale Bayesian linear inverse problems under reducible model uncertainty: good to know what you don't know. SIAM/ASA Journal on Uncertainty Quantification, 9(1), 163-184, 2021. [ preprint ]
  9. Alen Alexanderian. Optimal Experimental Design for infinite-dimensional Bayesian Inverse Problems Governed by PDEs: A Review. Inverse Problems. 2021. [ preprint ]
  10. E. Benjamin Randall, Nicholas Z. Randolph, Alen Alexanderian, and Mette S. Olufsen. Global sensitivity analysis informed model reduction and selection applied to a Valsalva maneuver model. Journal of Theoretical Biology 2021. [ preprint ]
  11. Rebekah White, Omid Yousefian, H.T. Banks, Alen Alexanderian, and Marie Muller. Inferring pore radius and density from ultrasonic attenuation using physics-based modeling. The Journal of the Acoustical Society of America, 2021. [ journal link ]
  12. Michael Merritt, Alen Alexanderian, and Pierre Gremaud. Multiscale global sensitivity analysis for stochastic chemical systems, SIAM Journal on Multiscale Modeling and Simulation, 2021. [ preprint ]
  13. Isaac Sunseri, Joseph Hart, Bart van Bloemen Waanders, and Alen Alexanderian. Hyper-Differential Sensitivity Analysis for Inverse Problems Constrained by Partial Differential Equations. Inverse Problems, 36(12), 2020. [  preprint  |  journal link  ]
  14. Karina Koval, Alen Alexanderian, and Georg Stadler. Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs. Inverse Problems, 36(7), 2020. [ preprint ]
  15. Hayley Guy, Alen Alexanderian, and Meilin Yu. A distributed active subspace method for scalable surrogate modeling of function valued outputs. Journal of Scientific Computing, 85(36), 2020. [ preprint ]
  16. Elizabeth Herman, Alen Alexanderian, and Arvind K. Saibaba. Randomization and reweighted $\ell_1$-minimization for A-optimal design of linear inverse problems. SIAM Journal on Scientific Computing, 42(3), A1714-A1740, 2020. [ preprint ]
  17. Alen Alexanderian, Pierre Gremaud, and Ralph C. Smith. Variance-based sensitivity analysis for time-dependent processes. Reliability Engineering & System Safety, 2020. [ preprint  | journal  ]
  18. Helen L. Cleaves, Alen Alexanderian, Hayley Guy, Ralph C. Smith, and Meilin Yu. Derivative based global sensitivity analysis for models with high-dimensional inputs and functional outputs. SIAM Journal on Scientific Computing, 41(6), A3524–A3551. 2019. [ preprint  | journal  ]
  19. Alen Alexanderian, William Reese, Ralph C. Smith, and Meilin Yu. Model input and output dimension reduction using Karhunen-Loève expansions with application to biotransport. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B: Mechanical Engineering, (5)4:041014, 2019. [ preprint  | journal  ]
  20. Manav Vohra, Alen Alexanderian, Hayley Guy, Sankaran Mahadevan. Active subspace-based dimension reduction for chemical kinetics applications with epistemic uncertainty. Combustion and Flame. 204:152–161, 2019. [ preprint  | journal  ]
  21. Arvind Saibaba, Jonathan Bardsley, Andrew Brown, Alen Alexanderian. Efficient marginalization-based MCMC Methods for hierarchical Bayesian inverse problems. SIAM Journal on Uncertainty Quantification, 7(3), 1105--1131, 2019. [ preprint  | journal ]
  22. Manav Vohra, Alen Alexanderian, Cosmin Safta, and Sankaran Mahadevan. Sensitivity-driven adaptive construction of reduced-space surrogates. Journal of Scientific Computing, 79(2):1335–1359, 2019. [ preprint  | journal  ]
  23. Alen Alexanderian and Arvind K. Saibaba. Efficient D-optimal design of experiments for infinite-dimensional Bayesian linear inverse problems. SIAM Journal on Scientific Computing, 40(5):A2956--A2985, 2018. [ preprint  | journal  ]
  24. Ahmed Attia, Alen Alexanderian, and Arvind K. Saibaba. Goal-Oriented Optimal Design of Experiments for Large-Scale Bayesian Linear Inverse Problems. Inverse Problems, 34(9). 2018. [ preprint  | journal  ]
  25. Bilal Saad, Alen Alexanderian, Serge Prudhomme, and Omar Knio. Probabilistic modeling and global sensitivity analysis for CO2 storage in geological formations: a spectral approach. Applied Mathematical Modelling, 53:584--601. 2018. [ preprint  | journal  ]
  26. Alen Alexanderian, Noemi Petra, Georg Stadler, and Omar Ghattas. Mean-variance risk-averse optimal control of systems governed by PDEs with random parameter fields using quadratic approximations. SIAM Journal on Uncertainty Quantification, 5(1):1166–1192. 2017. [ preprint  | journal  ]
  27. Joseph Hart, Alen Alexanderian, and Pierre Gremaud. Efficient computation of Sobol indices for stochastic models. SIAM Jounral on Scientific Computing. 39(4). 2017. [ preprint  |   journal ]
  28. Alen Alexanderian, Liang Zhu, Maher Salloum, Ronghui Ma, and Meilin Yu. Investigation of biotransport in a tumor with uncertain material properties using a non-intrusive spectral uncertainty quantification method. ASME Journal of Biomechanical Engineering, In press. 2017. [ preprint  |   journal ]
  29. Arvind K. Saibaba, Alen Alexanderian, and Ilse Ipsen. Randomized matrix-free trace and log-Determinant estimators. Numerische Mathematik, Numerische Mathematik. 137(2). 2017. [ preprint  |  journal ]
  30. Ben Crestel, Alen Alexanderian, Georg Stadler, and Omar Ghattas. A-optimal source encoding for inverse problems, with applications to seismic inversion. Inverse Problems, In press. 2017. [ preprint   journal ]
  31. Craig Michoski, Alen Alexanderian, Charles Paillet, Clint Dawson, and Ethan Kubatko. Stability of Nonlinear Convection–Diffusion–Reaction Systems in Discontinuous Galerkin Methods. Journal of Scientific Computing. 70(2):516-550. 2017. [ journal ]
  32. Alen Alexanderian, Noemi Petra, Georg Stadler, and Omar Ghattas. A fast and scalable method for A-optimal design of experiments for infinite-dimensional Bayesian nonlinear inverse problems. SIAM Journal on Scientific Computing, 38(1):A243-A272. 2016. [  preprint   journal  ]
  33. Alen Alexanderian, Philip Gloor, Omar Ghattas. On Bayesian A- and D-optimal experimental designs in infinite dimensions. Bayesian Analysis. 2016.. [ preprint  |  journal ]
  34. Alen Alexanderian. A primer on homogenization of elliptic PDEs with stationary and ergodic random coefficient functions. Rocky Mountain Journal of Mathematics. 2015. [  preprint  |  journal  ]
  35. Alen Alexanderian, Noemi Petra, Georg Stadler, and Omar Ghattas. A-Optimal design of experiments for infinite-dimensional Bayesian linear inverse problems with regularized $\ell_0$-sparsification. SIAM Journal on Scientific Computing. 36(5). 2014. [ preprint  |  journal ]
  36. Alen Alexanderian, Francesco Rizzi, Muruhan Rathinam, Olivier Le Maître, and Omar M. Knio. Preconditioned bayesian regression for stochastic chemical kinetics. Journal of Scientific Computing, 58(3):592-626, 2014. [ preprint  |  journal ]
  37. Alen Alexanderian. On spectral methods for variance based sensitivity analysis. Probability Surveys, Volume 10 (2013). [ preprint  |  journal ]
  38. Ihab Sraj, Mohamed Iskandarani, Ashwanth Srinivasan, Carlisle Thacker, Justin Winokur, Alen Alexanderian, Chiaying Lee, Shuyi Chen, and Omar M Knio. Bayesian Inference of Dependence of Drag Coefficient on Wind Speed using AXBT data from Typhoon Fanapi. Monthly Weather Review, 141(7):2347-2367, 2013. [ journal ]
  39. Alen Alexanderian, Justin Winokur, Ihab Sraj, Ashwanth Srinivasan, Mohamed Iskandarani, William C. Thacker, and Omar M. Knio. Global sensitivity analysis in an ocean general circulation model: A sparse spectral projection approach. Computational Geosciences, 16(3):757-778, 2012. [ reprint  |  journal ]
  40. Maher Salloum, Alen Alexanderian, Olivier Le Maître, Habib N. Najm, and Omar M. Knio. Simplified CSP analysis of a stiff stochastic ODE system. Computer Methods in Applied Mechanics and Engineering. 217-220:121–138, 2012. [  reprint  |  journal ]
  41. Alen Alexanderian, Olivier Le Maître, Habib Najm, Mohamed Iskandarani, and Omar Knio. Multiscale stochastic preconditioners in non-intrusive spectral projection. Journal of Scientific Computing, 50:306-340, 2012. [ preprint  |  journal ]
  42. Alen Alexanderian, Matthias K. Gobbert, K. Renee Fister, Holly Gaff, Suzanne Lenhart, and Elsa Schaefer. An age-structured model for the spread of epidemic cholera: Analysis and simulation. Nonlinear Analysis: Real World Applications, 12(6):3483-3498, 2011. [ preprint  |  journal ]
  43. Alen Alexanderian, Muruhan Rathinam, and Rouben Rostamian. Homogenization, symmetry, and periodization in diffusive random media. Acta Mathematica Scientia, 32(1):129-154, 2012. [ preprint ]
  44. Alen Alexanderian, Muruhan Rathinam, and Rouben Rostamian. Irreducibility of symmetry groups implies isotropy. Journal of Elasticity, 102(2), 2011. [ preprint  |  journal ]
  45. Daniel Mueller, George Dimitoglou, Benjamin Caplins, Juan Pablo Garcia Ortiz, Benjamin Wamsler, Keith Hughitt, Alen Alexanderian, Jack Ireland, Desmond Amadigwe, and Bernhard Fleck. Jhelioviewer - visualizing large sets of solar images using jpeg 2000. Computing in Science & Engineering, 11(5):38-47, 2009. [ reprint ]

    Peer-reviewed conference proceedings

  46. White, R.D., Yousefian, O., Alexanderian, A., and Muller, M. Modeling Frequency Dependent Ultrasound Attenuation in Cortical Bone: Solving Direct and Inverse Problems. In 2020 IEEE International Ultrasonics Symposium (IUS) (pp. 1-3). IEEE.
  47. Alen Alexanderian, William Reese, Ralph C. Smith, and Meilin Yu. Efficient uncertainty quantification for biotransport in tumors with uncertain material properties. (SB3C2017). 2018.
  48. Miao Lu, A. Alexanderian, Maher Salloum, Liang Zhu, Ronghui Ma, and M. L. Yu. Stochastic modeling of biotransport in a tumor with uncertain material properties. Summer Biomechanics, Bioengineering and Biotransport Conference. (SB3C2017). 2017.

    PhD Thesis

  49. Alen Alexanderian. Random composite media: Homogenization, modeling, simulation, and material symmetry. PhD Thesis. University of Maryland, Baltimore County. Available from:, Publication Number: AAT 3422788., 2010.

    Technical reports and conference proceedings

  50. Isaac Sunseri, and Alen Alexanderian On marginals of Gaussian random vectors. 2018. [ download pdf ]
  51. Alen Alexanderian. A brief note on the Karhunen-Loève expansion. 2016. [ arXiv ]
  52. Habib Najm, Bert Debusschere, Michael Eldred, Cosmin Safta, John Jakeman, David Higdon, James Gattiker, Roger Ghanem, Omar Knio, Alen Alexanderian, Youssef M. Marzouk, Tarek A. El Moselhy, Jinglai Li, Patrick R. Conrad, Tan Bui-Thanh, Omar Ghattas, James Martin, Robert Moser, Ernesto Prudencio, and Georg Stadler. Quantification of uncertainty in extreme scale computations (QUEST). In DOE Exascale Research Conference, 2012.
  53. Daniel Mueller, George Dimitoglou, Alen Alexanderian Juan Pablo Garcia Ortiz,Ludwig Schmidt,Vincent K. Hughitt,Jack Ireland, and Bernhard Fleck. A Novel Approach to Discovery and Image Access in the Petabyte Age. American Geophysical Union, Fall Meeting 2009.
  54. Vincent K. Hughitt, Jack Ireland, Daniel Mueller, George Dimitoglou, Juan Pablo Garcia Ortiz, Ludwig Schmidt, Benjamin Wamsler, Jaclyn Beck, Alen Alexanderian, and Bernhard Fleck. Browsing Very Large Image Archives Online Using JPEG 2000. American Geophysical Union, Fall Meeting 2009.
  55. Alen Agheksanterian and Matthias K. Gobbert. Modeling the spread of epidemic cholera: an age-structured model. Technical Report number TR2007­9, Department of Mathematics and Statistics, University of Maryland, Baltimore County, 2007.
  56. Alen Agheksanderian and George Dimitoglou. Algorithms paradigms and case studies as a problem-solving methodology. In ASEE Mid-Atlantic Section Spring 2005 Conference, Fairleigh Dickinson University Teaneck, NJ, April 2005.

    Technical notes and expository pieces

    Since my graduate students days, when doing research or studying a specific topic, I sometimes create detailed notes that I can refer to later. These notes mostly aim to provide a clear discussion of a single topic or a collection of results in a self-contained fashion; though they occasionally contain new observations or small extensions of known results which I either needed in my work, or just happened to notice. Over the years I have augmented these with notes coming from my teaching, and short notes I sometimes wrote to clarify questions that came up in conversations with colleagues. From time to time, I revisit individual notes and update them as needed. I place some of these notes here in case others may find them helpful also. Please email me should there be any questions or comments regarding these, and I would appreciate any suggestions to make these notes better.

      Numerical Analysis:

    • Dependence of simple eigenpairs to differentiable perturbations [download pdf].
    • A basic note on iterative matrix inversion [download pdf].
    • A basic note on convergence of quadrature formulas [download pdf].
    • Notes on Gaussian quadrature [download pdf].
    • A brief note on sparse grids [download pdf].
    • Notes on linear multistep methods [download pdf].
    • A basic note on QR factorization [download pdf].
    • Computing gradients and Hessians using the adjoint method [download pdf].


    • Rellich's Theorem and some of its applications [download pdf].
    • Groups of linear operators on Banach spaces [download pdf].
    • Some notes on Riemann-Lebesgue lemma [download pdf].
    • On continuous dependence of roots of polynomials on coefficients [download pdf].
    • On non-existence of a Lebesgue-like measure in infinite-dimension [download pdf].
    • A brief note on tensor products of Hilbert spaces [download pdf].
    • Optimization in infinite-dimensional Hilbert spaces [download pdf].
    • On compact operators [download pdf].
    • Approximate inversion of compact perturbations of identity. [download pdf].

      Probability, stochastic processes, and applications :

    • Gaussian Hilbert Spaces and Homogeneous Chaos: From theory to applications. [download pdf].
    • Some notes on asymptotic theory in probability [download pdf].
    • A brief note on stochastic homogenization in 1D [download pdf].
    • A brief note on the Karhunen-Loève expansion [ arXiv ].
    • Mean and variance of quadratic functionals of Gaussian random vectors [ download pdf ].


    • A basic note on group representations and Schur’s lemma [download pdf].
    • Some commutation theorems in finite-dimensional vector spaces [download pdf].
    • Matrix Lie groups and their Lie algebras [download pdf].


    • On Stability of linear complementarity systems [download pdf].
    • A basic note on single phase flow in porous media [download pdf].
    • Disease modeling with social distancing: application to COVID-19 [ download pdf ].
    • Sensitivity of estimating parameters in an SIR epidemic model to observed data at different times [download pdf].