The Computational Engineering Analysis & Design (CEAD) Lab at South Dakota Mines, led by Dr. Prashant K. Jha, addresses complex challenges in modeling, simulation, and design across engineering disciplines. Our work spans fracture and failure mechanics, functional soft materials such as magnetic and dielectric polymers, and the mechanics of granular and heterogeneous materials. We also develop neural operators and machine learning methods for scientific computing, with a focus on controlling and quantifying approximation errors. By combining advanced computational methods with innovative design strategies, we aim to deepen understanding of material behavior and deliver solutions for demanding real-world applications.

Focus areas

Fracture Mechanics: Fracture and fatigue in complex materials, e.g., soft composites, functional materials

Granular Media Mechanics: High and multi-fidelity mechanics simulation of particles under significant loading

Neural Networks/Operators for Scientific Computing: Application of neural operators as surrogate of PDE-based problems and error estimation and control of neural operator surrogates

Analysis and Design of Smart Materials: Microstructure-property relation and design of novel materials such as magnetically and electrically active soft materials

We are actively seeking enthusiastic undergraduate and graduate students interested in computational mechanics and applying advanced numerical and machine learning-based methods to problems in fracture mechanics, functional soft materials, and granular materials.

Interested candidates should email me here!

Latest Preprints

Prashant K. Jha, Patrick Diehl, Robert Lipton (2024). Nodal finite element approximation of peridynamics. CMAME.

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Prashant K. Jha (2023). Residual-based error corrector operator to enhance accuracy and reliability of neural operator surrogates of nonlinear variational boundary-value problems. CMAME.

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Prashant K. Jha, Timothy Breitzman, Kaushik Dayal (2023). Discrete-to-Continuum Limits of Long-Range Electrical Interactions in Nanostructures. ARMA.

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Lianghao Cao, Thomas O'Leary-Roseberry, Prashant K. Jha, J. Tinsley Oden, Omar Ghattas (2023). Residual-Based Error Correction for Neural Operator Accelerated Infinite-Dimensional Bayesian Inverse Problems. JCP.

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Prashant K. Jha, J. Tinsley Oden (2022). Goal-Oriented A-Posteriori Estimation of Model Error as an Aid to Parameter Estimation. JCP.

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Latest News

Prashant K. Jha

Oct 24, 2025 1 min read

Dr. Aalok Jha from Johns Hopkins University will join our lab as a Postdoctoral Fellow starting November 2025

We are excited to welcome Dr. Aalok Jha to Computational Engineering Analysis and Design (CEAD) Lab at South Dakota Mines as a Postdoctoral Fellow. Dr. Jha has a PhD from IIT Kanpur (Aerospace Engineering) and specializes in finite element modeling and mechanics of materials. Prior to joining our group, Dr. Jha worked at Johns Hopkins University as a Postdoctoral Fellow.

Prashant K. Jha

Sep 9, 2025 0 min read

PhD position available in CEAD Lab

Prashant K. Jha

Jun 6, 2025 1 min read

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!