Prashant K. Jha
Prashant K. Jha

Assistant Professor of Mechanical Engineering

About Me

I am an Assistant Professor in the Department of Mechanical Engineering at the South Dakota School of Mines and Technology. Before taking this position, I worked at the University of Portsmouth as a Mechanical Engineering Lecturer (Asst. Prof.). I received a Ph.D. in Civil and Environmental Engineering from 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 then moved to the Oden Institute at UT Austin to gain experience in the computational mechanics of multiphysics and complex systems.

My research interests include solids and granular media mechanics, fracture mechanics, multiphysics and multiscale modeling, and applications of neural networks to engineering problems. I am serving the Journal of Peridynamics and Nonlocal Modeling as one of the associate editors, the Journal of Open Source Software (JOSS) as topic editor, and I am an Editorial Board Member of Scientific Reports.

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Interests
  • Fracture Mechanics
  • Mechanics of Solids and Granular Media
  • Multiphysics and Multiscale Modeling
  • Scientific Machine Learning
  • Uncertainty Quantification
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

Recent News

NSF research grant awarded to work on multi-fidelity modeling using PeriDEM

A huge thank you to the National Science Foundation (NSF) for the ERI award (link)! The awarded amount is $200k over two years.

This project will focus on developing an Adaptive Multi-Fidelity Framework for Modeling Heterogeneous Materials Under Extreme Conditions. We will be pushing the boundaries of how we simulate granular media like sand and rocks under intense stress. The attached video shows a glimpse of our work with the PeriDEM model!

Virtual Thematic Conference (January 10 - 11, 2022) on Computational Oncology

With colleagues, Ernesto Lima and Chengyue Wu, at Oden Institute, we are organizing a virtual thematic conference on computational oncology. The event is supported by Biological Systems TTA in USACM. We have a greate lineup of speakers and very excited to bring experts in one platform to discuss the modeling and data related issues in modeling cancer.

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