Tan Bui-Thanh Associate Professor Endowed William J. Murray, Jr. Fellow in Engineering No. 4 Co-Director of the Center for Scientific Machine Learning at the Oden Institute Editorial Board member of the Elsevier Computers & Mathematics with Applications since 03/2021 Leader of Pho-Ices Group Department of Aerospace Engineering and Engineering Mechanics The Oden Institute for Computational Engineering and Sciences The University of Texas at Austin E-mail: tanbui@oden.utexas.edu Office: ASE 4.220 and POB 3.118 Phone: (512) 471-8176 and (512) 232-8179 Fax: (512) 471-8694

Honors Grants Publications Teaching Softwares CV

Education

Ph.D in Computational Fluid Dynamics, February 2004--May 2007

M.Eng. in High Performance Computation for Engineered System, July 2003

B.Eng. in Aeronautics (with honors), March 2001

Research Interests

• Inverse problems
• Uncertainty quantification
• Numerical analysis
• Numerical optimization
• Reduced-order modeling (model order reduction)
• Scientific computing
• Model-constrained Scientific Deep Learning (SciDL) Algorithms
• Quantum-accelerated SciDL algorithms for Digital Twins

Publications

Recent work

• Tan Bui-Thanh, Adjoint and Its roles in Sciences, Engineering, and Mathematics, SIAM Book in progress , 2024.

• L. Leticia Ramírez-Ramírez, José A. Montoya, Jesús F. Espinoza, Chahak Mehta, Albert Orwa Akuno, Tan Bui-Thanh, Use of mobile phone sensing data to estimate residence and mobility times in urban patches during the COVID-19 epidemic: The case of the 2020 outbreak in Hermosillo, Under Review , 2024.

• John Breedis, and Tan Bui-Thanh, Evaluating nAI and Quadrature Based Neural Networks, SIAM Undergraduate Research Online, Under Review , 2024.

• Jau-Uei Chen, Tamas Horvath, and Tan Bui-Thanh, A Divergence-Free and H(div)-Conforming Embedded-Hybridized DG Method for the Incompressible Resistive MHD equations, Computer Methods in Applied Mechanics and Engineering, Under Review , 2024.

• Hoang Tran; Hao Li; Vinh Ngoc Tran; Tam V Nguyen; Manh-Hung Le; Thanh Duc Dang; Hong Xuan; Hung T. Pham; Tan Bui-Thanh; L. Ruby Leung, Mid-range hourly weather forecasting using PredRNN with image preprocessing , Artificial Intelligence for the Earth Systems, Under Review , 2024.

2024

• Tri Pham, Quoc Nguyen, and Tan Bui-Thanh. Microseismic events based characterization of fractal fracture network, Accepted , 2024.

• Jau-Uei Chen, Shinhoo Kang, Tan Bui-Thanh, and John Shadid, Unified hp-HDG Frameworks for Friedrichs' PDE systems, Computer & Mathematics with Applicationsv, Volume 154, Pages 236-266, 15 January 2024.

• Bui-Thanh, T., A Unified and Constructive Framework for the Universality of Neural Networks, The IMA Journal of Applied Mathematics, hxad032 , November, 2023.

• Nguyen, H., and Bui-Thanh, T., Model-Constrained Deep Learning Approaches for Inverse Problems , SIAM Journal of Scientific Computing, 41(1), C77-C100 , January 2024.

2023

• Russell Philley, Hai V. Nguyen, and Tan Bui-Thanh, Model-constrained uncertainty quantification for scientific deep learning of inverse solutions, the XLIV Iberto-Latin American Congress on Computational Mechanics in Engineering, Refereed proceeding , November, 2023.

• Jonathan Wittmer, Jacob Badger, Hari Sundar, and Tan Bui-Thanh. An Autoencoder Compression Approach for Accelerating Large-scale Inverse Problems, Inverse Problems, 39 115009 , October, 2023.

• Albert Orwa Akuno, L. Leticia Ramirez-Ramirez, Chahak Mehta, Krishnanunni C.G., Bui-Thanh, T., and Jose Arturo Montoya, Multi-patch epidemic models with partial mobility, residency, and demography, , Chaos, Solitons & Fractals , Volume 173, August, 113690 , 2023.

• Jonathan Wittmer, Krishnanunni C.G, Hai V. Nguyen, and Tan Bui-Thanh. On Unifying Randomized Methods for Inverse Problems, Inverse Problems, Volume 39, Number 7 , 075010, June, 2023.

• Nguyen, H., and Bui-Thanh, T., A Model-Constrained Tangent Manifold Learning Approach for Dynamical Systems , International Journal of Computational Fluid Dynamics, 36(7) , 655-685, February 10, 2023.

• Muralikrishnan, S., Shannon, S., Bui-Thanh, T., and Shadid, J., A Multilevel Block Preconditioner for the HDG Trace System Applied to Incompressible Resistive MHD , Computer Methods in Applied Mechanics and Engineering, 401 , 115775, February 1, 2023.

2022

• Lee, J., Bui-Thanh, T., Villa, U., Ghattas, O., Forward and inverse modelings of fault transmissibility in subsurface flows, Computers & Mathematics with Applications, 128 , 354-367, December 15, 2022.

• Ella Steins, Tan Bui-Thanh, Michael Herty, and Siegfried Muller, Probabilistic Constrained Bayesian Inversion for Transpiration Cooling, , Int J Numer Meth Fluids, 94(12) , 2020– 2039, 2022.

• Bui-Thanh, T., Li, Q., and Zepeda-Nunez, L., Bridging and Improving Theoretical and Computational Electric Impedance Tomography via Data Completion, SIAM Journal on Scientific Computing, 44(3) , B668-B693, 2022.

• Wenbo Zhang, David S. Li, Tan Bui-Thanh, and Michael S. Sacks, Simulation of the 3D Hyperelastic Behavior of Ventricular Myocardium using a Finite-Element Based Neural-Network Approach, Computer Methods in Applied Mechanics and Engineering, Volume 394 , 114871, 2022.

• Hai Nguyen, Jonathan Wittmer, and Tan Bui-Thanh, DIAS: A Data-Informed Active Subspace regularization framework for inverse problems , MDPI Computation, 10 (38) , https://doi.org/10.3390/computation10030038, 2022.

2021

• Wenbo Zhang, David S. Li, Tan Bui-Thanh, and Michael S. Sacks, High-Speed Simulation of the 3D Behavior of Myocardium Using a Neural Network PDE Approach , Functional Imaging and Modeling of the Heart, Lecture Notes in Computer Science, Issue 6 , Editor: Ennis, Daniel B. and Perotti, Luigi E. and Wang, Vicky Y., page: 416--424, June, 2021.

• Bui-Thanh, T., The Optimality of Bayes' Theorem , SIAM News, Volume 54, Issue 6 , July/August, 2021.

• Goh, H., Sheriffdeen, S., Jonathan Wittmer, and Bui-Thanh, T., Solving Bayesian Inverse Problems via Variational Autoencoders , Proceeding of Machine Learning Research, 2nd Annual Conference on Mathematical and Scientific Machine Learning, Volume 145, August, 2021.

• Kang, S., and Bui-Thanh, T., A scalable exponential-DG approach for nonlinear conservation laws: with application to Burger and Euler equations , Computer Methods in Applied Mechanics and Engineering, Volume 385 , 1 November 2021, 114031.

• Zhang, W., Rossini, G., Bui-Thanh, T., and Sacks, M., The integration of structure and high-fidelity material models in heart valve simulations using machine learning , International Journal for Numerical Methods in Biomedical Engineering, Volume 37, Issue 4, e3438 , April 2021.

2020

• Jonathan Wittmer and Tan Bui-Thanh, Data-Informed Regularization For Inverse and Imaging Problems , Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, In Production , 2020.

• Ilona Ambartsumyan, Wajih Boukaram, Tan Bui-Thanh, Omar Ghattas, David Keyes, Georg Stadler, George Turkiyyah, and Stefano Zampini, Hierarchical Matrix Approximations of Hessians arising in Inverse Problems Governed by PDEs , SIAM Journal on Scientific Computing, , 42(5), A3397-A3426, 2020.

• Aaron Myers, Alexandre H. Thiery, Kainan Wang, and Tan Bui-Thanh, Sequential Ensemble Transform for Bayesian Inverse Problems , Journal of Computational Physics,110055, 2020.

2019

• Goh, H., Sheriffdeen, S., and Bui-Thanh, T., Solving Bayesian Inverse Problems via Autoencoders , 2019.

• Sheroze Sheriffdeen, Jean C. Ragusa, Jim E. Morel, Marvin L. Adams, and Tan Bui-Thanh, Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models , Submitted , 2019.

• Nick Alger, Vishwas Rao, Aaron Myers, Tan Bui-Thanh, and Omar Ghattas, Scalable matrix-free adaptive product-convolution approximation for locally translation-invariant operators , SIAM Journal on Scientific Computing, 41(4), A2296--A2328, 2019

• Muralikrishnan, S., Bui-Thanh, T., and Shadid, J., A Multilevel Approach for Trace System in HDG Discretizations, Journal of Computational Physics, 407, 109240, 2020.

• Wildey, T., Muralikrishnan, S., and Bui-Thanh, T., Unified geometric multigrid algorithm for hybridized high-order finite element methods, SIAM Journal on Scientific Computing, , 41(5), S172-S195, 2019.

• Kang, S., Giraldo, F.X., and Bui-Thanh, T., IMEX HDG-DG: a coupled implicit hybridized discontinuous Galerkin (HDG) and explicit discontinuous Galerkin (DG) approach for shallow water systems , Journal of Computational Physics, 401, 109010, 15 January 2020.

2018

• Lee, J., Shannon, S., Bui-Thanh, T., and Shadid, J., Analysis of an HDG method for linearized incompressible resistive MHD equations , SIAM Journal of Numerical Analysis , 57(4), 1697–1722, 2019.

• Kang, S., Bui-Thanh, T., and Arbogast, T., A hybridized discontinuous Galerkin method for a linear degenerate elliptic equation arising from two-phase mixtures , Comput. Methods Appl. Mech. Engrg ,350, pp. 315-336, 2019.

• Muralikrishnan, S., Tran, M.B., and Bui-Thanh, T., An improved iterative HDG approach for partial differential equations, Journal of Computational Physics , 367, pp. 295-321, 2018.

• Wang, K., Bui-Thanh, T., and Ghattas, O., A Randomized Maximum A Posteriori Method for Posterior Sampling of High Dimensional Nonlinear Bayesian Inverse Problems , SIAM Journal on Scientific Computing , 40(1), pp. A142--A171, 2018.

2017

• Alger, N., Villa, U., Bui-Thanh, T., and Ghattas, O., A Data Scalable Augmented Lagrangian KKT Preconditioner for Large-scale Inverse Problems , SIAM Journal on Scientific Computing , 39(5), pp. A2365-A2393, 2017.

• Lin, Y., Le, E.B., O'Malley, D., Vesselinov, V.V., and Bui-Thanh, T., Large-Scale Inverse Model Analyses Employing Fast Randomized Data Reduction , Water Resources Research , 53(8), pp. 6784--6801, 2017.

• Muralikrishnan, S., Tran, M-B, and Bui-Thanh, T., iHDG: an iterative HDG Framework for Partial Differential Equations , SIAM Journal on Scientific Computing , 39(5), pp. S782--S808, 2017.

• Le, E., Myers, A., Bui-Thanh, T., and Nguyen, Q. P., A Randomized Misfit Approach for Data Reduction in Large-Scale Inverse Problems , Inverse Problems , 33(6), 065003, 2017.

2016

• Bui-Thanh, T., Construction and Analysis of HDG Methods for Linearized Shallow Water Equations , SIAM Journal on Scientific Computing , 38(6),pp. A3696--A3719, 2016.

• Bui-Thanh, T., and Q. Nguyen, FEM-Based Discretization-Invariant MCMC Methods for PDE-constrained Bayesian Inverse Problems , Inverse Problems and Imaging , 10(4), pp. 943--975, 2016.

• Constantine, P.G., Kent, C., and Bui-Thanh, T., Accelerating MCMC with active subspaces , SIAM Journal on Scientific Computing , 38(5), pp. A2779--A2805 , 2016.

• Lan, S., Bui-Thanh, T., Christie, M., and Girolami, M., Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems , Journal of Computational Physics , 308, 81--101, 2016.

2015

• Bui-Thanh, T. , From Rankine-Hugoniot Condition to a Constructive Derivation of HDG Methods , in Lecture Notes in Computational Science and Engineering: Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2014 , 2015.

• Bui-Thanh, T., From Godunov to A Unified Hybridized Discontinuous Galerkin Framework , Journal of Computational Physics , 295, pp. 114-146, 2015.

• Wilcox, L., Stadler, G., Bui-Thanh, T., and Ghattas, O., Discretely exact derivatives for hyperbolic PDE-constrained optimization problems discretized by the discontinuous Galerkin method , Journal of Scientific Computing , 63, pp. 138--162, 2015.

• Bui-Thanh, T., and Ghattas, O., A Scalable MAP Solver for Bayesian Inverse Problems with Besov Priors , Inverse Problems and Imaging , 9(1), pp. 27--53, 2015.

• Bui-Thanh, T., and Ghattas, O., Bayes is Optimal , ICES report 15-04 , 2015.

2014

• Bui-Thanh, T., and Girolami, M., Solving Large-scale PDE-Constrained Bayesian Inverse Problems With Riemann Manifold Hamiltonian Monte Carlo , Inverse Problems, Special issue , 30, 114014, 2014.

• Bui-Thanh, T., and Ghattas, O., A PDE-constrained Optimization Approach to the Discontinuous Petrov-Galerkin Method with a Trust Region Inexact Newton-CG Solver , Comput. Methods Appl. Mech. Engrg. , 278, pp. 20--40, 2014.

• Bui-Thanh, T., and Ghattas, O., An Analysis of Infinite Dimensional Bayesian Inverse Shape Acoustic Scattering and its Numerical Approximation , SIAM Journal on Uncertainty Quantification , 2, pp. 203--222, 2014.

• Roberts, N., Bui-Thanh, T., and Demkowicz, D., The DPG Method for the Stokes Problem , Computers & Mathematics with Applications , 67, pp. 966--995, 2014.

• Chan, J., Heuer, N., Bui-Thanh, T., and Demkowicz, D., Robust DPG method for convection-dominated diffusion problems II: a natural in flow condition , Computers & Mathematics with Applications , 67, pp. 771--795, 2014.

2013

• Bui-Thanh, T., Ghattas, O., Martin, J., and Stadler, G., A computational framework for infinite-dimensional Bayesian inverse problems. Part I: The linearized case, with application to global seismic inversion , SIAM Journal on Scientific Computing , 35(6), pp. A2494--A2523, 2013.

• Bui-Thanh, T., and Ghattas, O., Analysis of the Hessian for Inverse Scattering Problems. Part III: Inverse Medium Scattering of Electromagnetic Waves in Three Dimensions , Inverse Problems and Imaging, 7(4), pp. 1139--1155, 2013.

• Bui-Thanh, T., Demkowicz, L., and Ghattas, O., A Unified Discontinuous Petrov-Galerkin Method and its Analysis for Friedrichs' Systems , SIAM Journal on Numerical Analysis , 51(4), pp. 1933--1958, 2013.

• Bui-Thanh, T., Demkowicz, L., and Ghattas, O., Constructively Well-Posed Approximation Methods with Unity Inf-Sup and Continuity Constants for Partial Differential Equations , Mathematics of Computation , 82(284), pp. 1923--1952, 2013.

2012

• Bui-Thanh, T., Burstedde, C., Ghattas, O., Martin, J., Stadler, G., and Wilcox, L.C., Extreme-scale UQ for Bayesian inverse problems governed by PDEs , ACM/IEEE Supercomputing SC12, Gordon Bell Prize Finalist , Salt Lake City, Utah, 2012.

• Bui-Thanh, T., and Ghattas, O., A Scaled Stochastic Newton Algorithm for Markov Chain Monte Carlo Simulations , SIAM Journal on Uncertainty Quantification , Submitted, 2012.

• Bui-Thanh, T., A Gentle Tutorial on Statistical Inversion using the Bayesian Paradigm , ICES Report 12-18 , 2012.

2011

• Bui-Thanh, T., Ghattas, O., and Higdon, D., Adaptive Hessian-based Non-stationary Gaussian Process Response Surface Method for Probability Density Approximation with Application to Bayesian Solution of Large-scale Inverse Problems , SIAM Journal on Scientific Computing , 34(6), pp. A2837--A2871, 2012.

• Bui-Thanh, T., and Ghattas, O., Analysis of the Hessian for Inverse Scattering Problems. Part I: Inverse Shape Scattering of Acoustic Waves , In 2013 Highlight Collection of Inverse Problems, 28, 055001, 2012.

• Bui-Thanh, T., and Ghattas, O., Analysis of the Hessian for Inverse Scattering Problems. Part II: Inverse Medium Scattering of Acoustic Waves , Inverse Problems, 28, 055002, 2012.

• Bui-Thanh, T., and Ghattas, O., An Analysis of a Non-conforming hp-Discontinuous Galerkin Spectral Element Method for Wave Propagations , SIAM Journal on Numerical Analysis , 50(3), pp. 1801--1826, 2012.

Selected publications prior to 2011

• Bui-Thanh, T., Demkowicz, L., and Ghattas, O., A Relation between the Discontinuous Petrov--Galerkin Method and the Discontinuous Galerkin Method , ICES Report ICES 11-45 , December, 2011.

• Wadley, H.N.G., Dharmasena, K.P., He, M.Y., McMeeking, R. M., Evans, A. G., Bui-Thanh, T., and Radovitzky, R., An active concept for limiting injuries caused by air blasts , International Journal of Impact Engineering, 37(3), pp. 317--323, 2010.

• Bui-Thanh, T., Willcox, K., and Ghattas, O., Parametric Reduced-Order Models for Probabilistic Analysis of Unsteady Aerodynamic Applications , AIAA Journal , 46(10), pp. 2520--2529, 2008.

• Bui-Thanh, T., Willcox, K., and Ghattas, O., Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space , SIAM Journal on Scientific Computing , 30(6), pp. 3270--3288, 2008.

• Bui-Thanh, T., Willcox, K., Ghattas, O., van Bloemen Waanders, B., Goal-Oriented, Model-Constrained Optimization for Reduction of Large-Scale Systems , Journal of Computational Physics , Vol. 224, pp. 880--896, 2007.

• Bui-Thanh, T., Damodaran, M. and Willcox, K., Aerodynamic Data Reconstruction and Inverse Design using Proper Orthogonal Decomposition , AIAA Journal , 42(8), pp. 1505--1516, 2004.

• Bui-Thanh, T., Model-Constrained Optimization Methods for Reduction of Parameterized Large-Scale Systems , Ph.D thesis , Department of Aeronautics and Astronautics, MIT, 2007.

• Bui-Thanh, T., Proper Orthogonal Decomposition Extensions and Their Applications in Steady Aerodynamics , Master thesis , High Performance Computation for Engineered Systems, Singapore-MIT Alliance, 2003.

Awards and Honors

• Elected Secretary of the SIAM SIAG-CSE (2020-2022)
• Elected Vice President of the SIAM Texas-Louisiana Section (2020-2022)
• Endowed William J. Murray, Jr. Fellow in Engineering No. 4, 2020
• Moncrief Grand Challenges Faculty Award, 2019
• NSF Career Award (jointly by NSF-OAC and NSF-DMS), 2019
• Summer Faculty fellowship, Air Force Office of Scientific Research (AFOSR), 2016
• Moncrief Grand Challenges Faculty Award, 2014
• DSO National Lab Award for the best master's thesis, Singapore, 2003.
• IHPC-SUN Award for the best student in ``Introduction to Numerical Simulation'', Singapore, 2002.
• Silver medal in Fluid Mechanics in national Olympic competition, Vietnam, 1999.
• ROtring Merit award for topscorer in the intake examination, Ho Chi Minh City University of Technology, Vietnam, 1998.
• Best student, Ho Chi Minh City National University, Vietnam, 1997.
• Best student, Ho Chi Minh City National University, Vietnam, 1996.

Fundings

• Our research is supported by the US Department of Energy, National Science Foundation, Raytheon Technologies, NASA fellowship, and UT-Portugal.

Softwares

• STIRNCG : 2005-present, a subspace trust region interior reflective inexact Newton-CG solver for optimization problems with bound constraints. This code is written in Matlab, and a C version is implemented in libmaoi .
• mangll : 2008-present (with Lucas C. Wilcox, Georg Stadler, Carsten Burstedde, Tobin Isaac, and James Martin), a high-order h-adaptive continuous and discontinuous finite element discretization library that is highly scalable.
• libsc : 2010-present (with Carsten Burstedde, Lucas C. Wilcox, Tobin Isaac, and James Martin), an MPI-based C-library that provides basic data structures and common facilities for parallel generic and scientific computing. libsc is released under the GNU LGPL version 2.1 (or later) and distributed with p4est .
• libmaoi : 2010-present (with Carsten Burstedde, Georg Stadler, and James Martin), a C library to provide abstract optimization algorithms.

Teaching

• Mathematical Methods in Applied Mechanics
• Applied Mathematics