35 citations · 209 across the 15 of their papers we have counts for
16 papers
Bridging Scales: a Hybrid Model to Simulate Vascular Tumor Growth and Treatment Response
Tobias Duswald, Ernesto A. B. F. Lima, J. Tinsley Oden +1
Cancer is a disease driven by random DNA mutations and the interaction of many complex phenomena. To improve the understanding and ultimately find more effective treatments, resear…
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data and machine learning surrogate
Lianghao Cao, Keyi Wu, J. Tinsley Oden +2
Identifying parameters of computational models from experimental data, or model calibration, is fundamental for assessing and improving the predictability and reliability of comput…
A phase-field model for non-small cell lung cancer under the effects of immunotherapy
Andreas Wagner, Pirmin Schlicke, Marvin Fritz +4
Formulating tumor models that predict growth under therapy is vital for improving patient-specific treatment plans. In this context, we present our recent work on simulating non-sm…
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems
Lianghao Cao, Thomas O'Leary-Roseberry, Prashant K. Jha +2
We explore using neural operators, or neural network representations of nonlinear maps between function spaces, to accelerate infinite-dimensional Bayesian inverse problems (BIPs)…
Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm
Dingcheng Luo, Lianghao Cao, Peng Chen +2
Directed self-assembly (DSA) of block-copolymers (BCPs) is one of the most promising developments in the cost-effective production of nanoscale devices. The process makes use of th…
Mutual-Information Based Optimal Experimental Design for Hyperpolarized C-Pyruvate MRI
Prashant K. Jha, Christopher Walker, Drew Mitchell +4
A key parameter of interest recovered from hyperpolarized (HP) MRI measurements is the apparent pyruvate-to-lactate exchange rate, , for measuring tumor metabolism. This ma…
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
Ricardo Baptista, Lianghao Cao, Joshua Chen +4
We consider the Bayesian calibration of models describing the phenomenon of block copolymer (BCP) self-assembly using image data produced by microscopy or X-ray scattering techniqu…
Goal-Oriented A-Posteriori Estimation of Model Error as an Aid to Parameter Estimation
Prashant K. Jha, J. Tinsley Oden
In this work, a Bayesian model calibration framework is presented that utilizes goal-oriented a-posterior error estimates in quantities of interest (QoIs) for classes of high-fidel…
Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett +6
Current clinical decision-making in oncology relies on averages of large patient populations to both assess tumor status and treatment outcomes. However, cancers exhibit an inheren…
Modeling and simulation of vascular tumors embedded in evolving capillary networks
Marvin Fritz, Prashant K. Jha, Tobias Köppl +3
In this work, we present a coupled 3D-1D model of solid tumor growth within a dynamically changing vascular network to facilitate realistic simulations of angiogenesis. Additionall…
A globally convergent modified Newton method for the direct minimization of the Ohta-Kawasaki energy with application to the directed self-assembly of diblock copolymers
Lianghao Cao, Omar Ghattas, J. Tinsley Oden
We propose a fast and robust scheme for the direct minimization of the Ohta-Kawasaki energy that characterizes the microphase separation of diblock copolymer melts. The scheme empl…
Analysis of a new multispecies tumor growth model coupling 3D phase-fields with a 1D vascular network
Marvin Fritz, Prashant K. Jha, Tobias Köppl +2
In this work, we present and analyze a mathematical model for tumor growth incorporating ECM erosion, interstitial flow, and the effect of vascular flow and nutrient transport. The…
A statistical framework for generating microstructures of two-phase random materials: application to fatigue analysis
Ustim Khristenko, Andrei Constantinescu, Patrick Le Tallec +2
Random microstructures of heterogeneous materials play a crucial role in the material macroscopic behavior and in predictions of its effective properties. A common approach to mode…
Local and nonlocal phase-field models of tumor growth and invasion due to ECM degradation
Marvin Fritz, Ernesto A. B. F. Lima, Vanja Nikolić +2
We present and analyze new multi-species phase-field mathematical models of tumor growth and ECM invasion. The local and nonlocal mathematical models describe the evolution of volu…
On the unsteady Darcy-Forchheimer-Brinkman equation in local and nonlocal tumor growth models
Marvin Fritz, Ernesto A. B. F. Lima, J. Tinsley Oden +1
A mathematical analysis of local and nonlocal phase-field models of tumor growth is presented that includes time-dependent Darcy-Forchheimer-Brinkman models of convective velocity…
Research and Education in Computational Science and Engineering
Ulrich Rüde, Karen Willcox, Lois Curfman McInnes +30
Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance…