Research
Applications

Inversion for optical properties of biological tissues in quantitative optoacoustic tomography

Bayesian optimal experimental design for inverse problems in acoustic scattering

Inversion and control for CO_{2} sequestration with poroelastic models

Goaloriented inference for reservoir models with complex features including faults

Joint seismicelectromagnetic inversion

Inference of basal boundary conditions for ice sheet flow

Inversion for coupled iceocean interaction

Inversion for material properties of cardiac tissue

Inference, prediction and optimization under uncertainty for turbulent combustion

Inference of constitutive laws in mechanics of nanoscale filaments
Publications

R. Nicholson, N. Petra and Jari P Kaipio. Estimation of the Robin coefficient field in a Poisson problem with uncertain conductivity field, Inverse Problems, Volume 34, Number 11, 2018.

P. Chen, K. Wu, J. Chen, T. O'LearyRoseberry, O. Ghattas, Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions, arXiv, 2018

E. M. Constantinescu, N. Petra, J. Bessac, C. G. Petra, Statistical Treatment of Inverse Problems Constrained by Differential EquationsBased Models with Stochastic Terms, arXiv, 2018

P. Chen, U. Villa, O. Ghattas, Taylor approximation and variance reduction for PDEconstrained optimal control under uncertainty, ArXiv, 2018

U. Villa, N. Petra, O. Ghattas, hIPPYlib: An extensible software framework for largescale inverse problems; Part I: Deterministic inversion and linearized Bayesian inference, in preparation, 2018

U. Villa, N. Petra, O. Ghattas, hIPPYlib: An extensible software framework for largescale inverse problems, Journal of Open Source Software (JOSS), 3(30):940, 2018

P. Chen, U. Villa, O. Ghattas, Taylor approximation for PDEconstrained optimization under uncertainty: Application to turbulent jet flow, Proceedings in Applied Mathematics and Mechanics  89th GAMM Annual Meeting, accepted, 2018
Ph.D. Thesis

K. A. McCormack, Earthquakes, groundwater and surface deformation: exploring the poroelastic response to megathrust earthquakes, University of Texas at Austin, 2018. Adviser M. Hesse

B. Crestel, Advanced techniques for multisource, multiparameter, and multiphysics inverse problems, University of Texas at Austin, 2017. Adviser O. Ghattas
Oral Presentations

I. Ambartsumyan, O. Ghattas, Fast methods for Bayesian inverse problems governed by PDE forward models with random coefficient fields, Applied Inverse Problems Conference, July 812, 2019, Grenoble, France

U. Villa, O. Ghattas, Scalable optimal experimental design for large scale nonlinear Bayesian inverse problems, Applied Inverse Problems Conference, July 812, 2019, Grenoble, France

O. Babaniyi, O. Ghattas, N. Petra and U. Villa, hIPPYlib: An Extensible Software Framework for LargeScale Inverse Problems, 2019 FEniCS Conference, Carnegie Institution for Science Department of Terrestrial Magnetism (DTM), Washington DC,June 1214, 2019. Best postdoc presentation award

N. Petra, G. Stadler, Inverse Problems: Integrating Data with Models under Uncertainty, SIAM CSE, Feb 25March 1, 2019, Spokane, Wa, US

K. Wu, P. Chen, O. Ghattas,A Stein Variational Newton Method for Optimal Experiment Design Problems, SIAM CSE, Feb 25March 1, 2019, Spokane, Wa, US

P. Chen, O. Ghattas, U. Villa, Largescale Optimal Experimental Design for Bayesian Nonlinear Inverse Problems, SIAM CSE, Feb 25March 1, 2019, Spokane, Wa, US

T. O'LearyRoseberry, J. Chen, P. Chen, U. Villa, O. Ghattas, Largescale Optimization in Deep Learning for PDE Representation abstract, SIAM CSE, Feb 25March 1, 2019, Spokane, Wa, US

J. J. Lee, O. Ghattas, T. BuiThanh, U. Villa, Derivative Informed MCMC Methods for Subsurface Models with Faults, SIAM CSE, Feb 25March 1, 2019, Spokane, Wa, US

U. Villa, O. Ghattas, Scalable Methods for Bayesian Optimal Experimental Design Using Laplace Approximation, SIAM CSE, Feb 25March 1, 2019, Spokane, Wa, US

U. Villa, Learning from data through the lens of mathematical models, Analysis Seminar, Dept. of Mathematics & Statistics, Washington University, January 28, 2019, St Louis, MO, US

U. Villa, Large Scale Inverse Problems and Uncertainty Quantification: Computational Tools and Imaging Applications, Electrical & Systems Engineering Seminar, Washington University, January 24, 2019, St Louis, MO, US

N. Petra, hIPPYlib: An Extensible Software Framework for LargeScale Inverse Problems, Optimization Seminar, University of California, Merced, October 19, 2018, Merced, CA, US

U. Villa, O. Ghattas, Maximize the Expected Information Gain in Bayesian Experimental Design Problems: A Fast Optimization Algorithm Based on Laplace Approximation and Randomized Eigensolvers, SIAM UQ, April 1619, 2018, Garden Grove, CA, US

T. O’LearyRoseberry, A PDE Constrained Optimization Approach to the Solution of the Stefan Problem, Texas Applied Mathematics and Engineering Symposium, Sept. 2123, 2017, Austin, TX, US

U. Villa, hIPPYlib: An Extensible Software Framework for LargeScale Deterministic and Linearized Bayesian Inverse, Texas Applied Mathematics and Engineering Symposium, Sept. 2123, 2017, Austin, TX, US

U. Villa, Taylor Approximation for PDEconstrained Optimal Control Problems under Highdimensional Uncertainty, SIAM Control, July 10  12, 2017, Pittsburgh, Pa, US

U. Villa, DerivativeInformed MCMC for Bayesian Calibration of Stochastic PDE Models, SIAM Annual, July 10  14, 2017, Pittsburgh, Pa, US

U. Villa, Hessianbased sampling techniques for Bayesian inverse problems with stochastic PDE forward model, Applied Inverse Problems, May 29  June 2, 2017, Hangzhou, China

U. Villa, Bayesian Calibration of Inadequate Stochastic PDE Models, SIAM CSE, Feb 27March 3, 2017, Atlanta, GA, US

P. Chen, Taylor Approximation for PDEConstrained Optimal Control Problems Under HighDimensional Uncertainty: Application to a Turbulence Model, SIAM CSE, Feb 27March 3, 2017, Atlanta, GA, US

B. Crestel, Scalable Solvers for Joint Inversion with Several Structural Coupling Terms, SIAM CSE, Feb 27March 3, 2017, Atlanta, GA, US

Amal Alghamdi, Bayesian Inversion for Subsurface Properties from Poroelastic Forward Models and Surface Deformation Data, SIAM CSE, Feb 27March 3, 2017, Atlanta, GA, US

U. Villa, An Analytical Technique for Forward and Inverse Propagation of Uncertainty, SIAM UQ, April 58, 2016, Lausanne, Switzerland
Poster Presentations

I. Ambartsumyan, T. BuiThanh, O. Ghattas, E. Khattatov, An Edgepreserving Method for Joint Bayesian Inversion with NonGaussian Priors, SIAM CSE, Feb 25 March 1, 2019, Spokane, Wa, US

E. Khattatov, O. Ghattas, T. BuiThanh, and I. Ambartsumyan, U. Villa, Bayesian Inversion of Fault Properties in Twophase Flow in Fractured Media, SIAM CSE, Feb 25 March 1, 2019, Spokane, Wa, US

A. O. Babaniyi, O. Ghattas, N. Petra, U. Villa, hIPPYlib: An Extensible Software Framework for Largescale Inverse Problems, SIAM CSE, Feb 25 March 1, 2019, Spokane, Wa, US

O. Ghattas, Y. Marzouk, M. Parno, N. Petra, U. Villa, Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for LargeScale Bayesian Inversion, NSFSI2 PI meeting, Apr. 30 May 1, 2018, Washington, DC, US

K. Koval, G. Stadler, Computational Approaches for Linear GoalOriented Bayesian Inverse Problems, SIAM Annual, July 10  14, 2017, Pittsburgh, Pa, US

J. Chen, A. Drach, U. Villa, R. Avazmohammadi, D. Li, O. Ghattas and M. Sacks, Identification of Mechanical Properties of 3D Myocardial Tissue: An Inverse Modeling and Optimal Experimental Design Problem, FEniCS'17, June 1214, 2017, University of Luxembourg, Luxembourg

T. O’LearyRoseberry, U. Villa, O. Ghattas, P. Heimbach, An Adjoint Capable Solver for the Stefan Problem: a Bilevel Optimization and Level Set Approach, SIAM CSE, Feb. 27  March 3, 2017, Atlanta, GA, US

O. Ghattas, Y. Marzouk, M. Parno, N. Petra, U. Villa, Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for LargeScale Bayesian Inversion, NSFSI2 PI meeting, Feb. 2122, 2017, Arlington, VA, US
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