Prashant K. Jha

Prashant K. Jha

Research Associate

The University of Texas at Austin


I am a Research Associate at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin. I received a Ph.D. from Carnegie Mellon University in August 2016. I then worked as a Postdoctoral Scholar at the Department of Mathematics, Louisiana State University.

Current work includes developing models of tumor growth and recovery of model parameters from the imaging data. Of particular interest is angiogenesis, where new blood vessels are formed (and destroyed) in response to various signals from the nutrient-starved tumor cells. We recently got a small grant to develop a PDE-based model for Hyperpolarized (HP) MRI signal recovery. The work on HP MRI is done in collaboration with researchers at the MD Anderson Cancer Center. In addition, I have recently become interested in granular media and associated challenges in model development. Towards this, we have developed a high-fidelity model PeriDEM that can handle individual deformation and breakage of arbitrarily shaped particles and the contacts between deforming bodies.

I will be teaching two courses during Fall 2021 at UT Austin. The two subjects are Engineering Computation in Aerospace Engineering and Engineering Mechanics and Introduction to Numerical Methods in Biomedical Engineering in Biomedical Engineering. I am serving the Journal of Peridynamics and Nonlocal Modeling as one of the associate editors.


  • Mechanics of Solids and Granular Media
  • Computational Oncology
  • Multiscale Modeling
  • Artificial Neural Networks


  • PhD in Civil and Environmental Engineering, 2016

    Carnegie Mellon University, Pittsburgh, USA

  • ME in Mechanical Engineering, 2012

    Indian Institute of Science, Bangalore, India

  • BE in Mechanical Engineering, 2010

    Govt. Engineering College, Raipur, India



Research Associate

The University of Texas at Austin

Nov 2020 – Present Austin

Postdoctoral Scholar

The University of Texas at Austin

Aug 2019 – Nov 2020 Austin

Postdoctoral Scholar

Louisiana State University

Oct 2016 – Jul 2019 Baton Rouge

Professional Responsibilities

1. Associate Editor

Journal of Peridynamics and Nonlocal Modeling

2. Journal Reviews



1. COE 311K – Engineering Computation (Fall 2021)

Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin

2. COE 313L – Introduction to Numerical Methods in Biomedical Engineering (Fall 2021)

Department of Biomedical Engineering, The University of Texas at Austin


1. $50,000 (Sep 2020 – Aug 2021)

Title: A mechanistic tumor growth model for HP MRI

Awarded under the MDACC-Oden-TACC joint initiative.


Computational methods for nonlocal models

Develop efficient and parallel computational methods for class of nonlocal models such as Peridynamics and nonlocal diffusion equations

Analysis and application of peridynamics

Analysis and application of peridynamics

Modeling tumor growth, angiogenesis, drug-therapy, metastasis

Development and analysis of models of tumor growth, angiogenesis, drug therapy, and metastasis

Signal recovery from MRI

Development of models for improved signal recovery and image reconstruction, and developement and application of new methods for optimal data acquisition with uncertain model parameters

Study of granular media

Study properties of granular media using computational methods

Recent Publications

Modeling and simulation of vascular tumors embedded in evolving capillary networks
Biologically-based mathematical modeling of tumor vasculature and angiogenesis via time-resolved imaging data



3D-1D tumor growth model for simulation of angiogenesis


Peridynamics-based discrete element method for granular media


Nonlocal mechanics library for peridynamics simulation


Calibration of SEIRD model under uncertainty: Application of Bayesian statistics


Solver for multidimensional flow model in python using Petsc and Fenics


Implementation of a distributed nonlocal heat equation solver with load balancing

Recent & Upcoming Talks

Model selection and optimal experiment design for HP MRI experiments

Hyperpolarized (HP) MR imaging provides enhanced insights into the tissue’s metabolism and a new way to identify the tumor …

Analysis and application of peridynamics to fracture in solids and granular media

In this talk, we will present our recent work on peridynamics and its application. We consider a bond-based peridynamics with a …

Phase Field Models of the Growth of Tumors Embedded in an Evolving Vascular Network: Dynamic 1D-3D Models of Angiogenesis

In this talk, we present a coupled 3D-1D model of tumor growth within a dynamically changing vascular network to facilitate realistic …