Prashant K. Jha

Prashant K. Jha

Research Associate

The University of Texas at Austin

Biography

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 Civil and Environmental Engineering, Carnegie Mellon University, in August 2016. After finishing my Ph.D., I joined the Department of Mathematics at Louisiana State University as a Postdoctoral Fellow and worked on numerical methods and analysis of the peridynamics theory of fracture. I moved to UT Austin in August 2019 to further expand my expertise and knowledge in computational mechanics. My research interests include solids and granular media mechanics, computational oncology, uncertainty quantification, and multiscale modeling.

Last year in Fall, I taught two undergraduate courses on numerical methods. I am also serving the Journal of Peridynamics and Nonlocal Modeling as one of the associate editors and the Journal of Open Source Software (JOSS) as topic editor.

Interests

  • Mechanics of Solids and Granular Media
  • Computational Oncology
  • Uncertainty Quantification
  • Multiscale Modeling
  • Application of Neural Networks to Mechanics Problems

Education

  • 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

Experience

 
 
 
 
 

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 (JPER)

2. Topic Editor

Journal of Open Source Software (JOSS)

3. Journal Reviews

CMAME, JMPS, SINUM, M3AS, JALCOM, PHYSA, Mathematical Reviews (AMS)

Grants

A mechanistic tumor growth model for HP MRI

With David Fuentes at MD Anderson Cancer Center, Houston, USA. Awarded under the MDACC-Oden-TACC joint initiative.

$50,000 (Sep 2020 – Aug 2021)

Recent Publications

(2022). Goal-Oriented A-Posteriori Estimation of Model Error as an Aid to Parameter Estimation. Journal of Computational Physics.

PDF Source Document DOI

(2021). Peridynamics-based discrete element method (PeriDEM) model of granular systems involving breakage of arbitrarily shaped particles. Journal of the Mechanics and Physics of Solids.

PDF Source Document DOI

(2020). Kinetic relations and local energy balance for LEFM from a nonlocal peridynamic model. International Journal of Fracture.

PDF Source Document DOI

(2020). Discrete-to-Continuum Limits of Long-Range Electrical Interactions in Nanostructures. Under review.

Preprint PDF

Projects

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

Softwares

Angiogenesis3D1D

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

PeriDEM

Peridynamics-based discrete element method for granular media

NLMech

Nonlocal mechanics library for peridynamics simulation

BayesForSEIRD

Calibration of SEIRD model under uncertainty: Application of Bayesian statistics

nonlocalheatequation

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 …

Contact

  • 6.252 POB, Austin, TX 78712