About
Welcome to my homepage! I am Nishan Parvez, a postdoctoral researcher at Children’s Hospital of Philadephia. I received my PhD in Mechanical Engineering from Rensselaer Polytechnic Institute. My research interests lie in the broad domain of computational solid mechanics, with extensive research experience in computational modeling and analysis of large deformation and damage in soft materials (e.g., soft tissue, paper, hydrogels, etc.) using FEA and Machine Learning techiniques.
My current research focus is on the computational modeling of heart valve deformation in my role as Postdoc Research Fellow at Children’s Hospital at Philadephia. The up-to-date list of my published works is available at google scholar. Please feel free to browse around or contact me for questions related to my work.
Research Highlights
Non-linear elasticity of soft materials: In contrast to traditional engineering materials, soft materials can sustain very large deformation. Examples include soft biological tissue, e.g., skin, composed of microscale fibers organized in a network-like fashion. This project explores several aspect of this, including the origin of non-linear constitutive behavior, structure-property relations, and the implications of the microstructure under purely elastic deformations.
Publlished work on this topic:
- Stiffening mechanisms in stochastic athermal fiber networks. N Parvez, J Merson, C Picu; PRE,2023. DOI: https://doi.org/10.1103/PhysRevE.108.044502
- Effect of connectivity on the elasticity of athermal network materials. N Parvez, C Picu; Soft Matter, 2023. DOI: https://doi.org/10.1039/D2SM01303G
- Probing soft fibrous materials by indentation. J Merson, N Parvez, C Picu; Acta Biomaterialia, 2023. DOI: https://doi.org/10.1016/j.actbio.2022.03.053
A brief discussion on role of plasticity in these materials is available in-
- Nonlinear behavior of stochastic athermal fiber networks with elastic–plastic fibers. S Amjad, N Parvez, C Picu; Soft Matter, 2025. DOI: https://doi.org/10.1039/D4SM01427H
Constitutive modeling of fibrous materials using neural network: This project introduced a neural network-based surrogate computational model that accurately predicts the mechanical response of soft network materials within a continuum mechanics framework. The developed surrogate material model allows very efficient FEA simulation of soft material with few orders of magnitude cost reduction compared to hierarchial multiscale approach while maintaining remakable accuracy.
Publlished work on this topic:
- A physics preserving neural network based approach for constitutive modeling of isotropic fibrous materials. N Parvez, J Merson; Engineering with Computers, 2025. DOI: https://doi.org/10.1007/s00366-024-02095-8
Mechanism of damage and fracture in soft network materials: Soft materials exhibit novel failure behavior compared to traditional engineering materials due to non-linear deformation and other microstructural features. This leads to phenomena such as notch insensitivity, transition in the microscale failure mechanism, crack tip blunting, crack deflection etc. in these materials. This project explores various aspects of these behavior with primary focus on their mechanical origin and practical implications.
Publlished work on this topic:
- Crack Deflection and Toughening in Network Materials With Preferential Fiber Alignment. S Amjad, N Parvez, C Picu; JAM, 2025. DOI: https://doi.org/10.1115/1.4070021
- Crack Insensitivity and Brittle to Ductile Transition in Network Materials. N Parvez, C Picu JMPS, 2025. DOI: https://doi.org/10.1016/j.jmps.2025.106398
- Failure mechanism in stochastic network materials: The competition between fiber and crosslink failure. N Parvez, C Picu; IJSS, 2025. DOI: https://doi.org/10.1016/j.ijsolstr.2025.113445
Last Updated: Jan, 2024 | Powered by Ankit Sultana’s Researcher theme