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 (SIAM J. Sci. Comput., 2022)

Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data. - Lianghao Cao; Keyi Wu; J. Tinsley Oden; Peng Chen 024; Omar Ghattas (CoRR, 2023)

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems. - Lianghao Cao; Thomas O'Leary-Roseberry; Prashant K. Jha; J. Tinsley Oden; Omar Ghattas (J. Comput. Phys., 2023)

Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm. - Dingcheng Luo; Lianghao Cao; Peng Chen 024; Omar Ghattas; J. Tinsley Oden (J. Comput. Phys., 2023)

Efficient geometric Markov chain Monte Carlo for nonlinear Bayesian inversion enabled by derivative-informed neural operators. - Lianghao Cao; Thomas O'Leary-Roseberry; Omar Ghattas (CoRR, 2024)

LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport. - Lianghao Cao; Joshua Chen; Michael Brennan; Thomas O'Leary-Roseberry; Youssef M. Marzouk; Omar Ghattas (CoRR, 2024)

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; Omar Ghattas; Fengyi Li; Youssef M. Marzouk; J. Tinsley Oden (J. Comput. Phys., 2024)

Learning Memory and Material Dependent Constitutive Laws. - Kaushik Bhattacharya; Lianghao Cao; George Stepaniants; Andrew M. Stuart; Margaret Trautner (CoRR, 2025)