Applied Machine Learning · Finite Elements

Bhavesh Shrimali

Senior Engineer, Advanced Modeling and AI Solutions at Micron Technology

At Micron Technology, I develop advanced modeling and AI solutions for semiconductor manufacturing. I combine physics-based and ML-driven process models—especially hybrid Physics+AI approaches—with high-fidelity nonlinear finite-element analysis (FEA), numerical simulation, and deep learning to represent complex manufacturing behavior, construct efficient surrogates, quantify uncertainty, and support engineering decisions.

My technical work spans high-performance finite-element and multiphysics simulation; scientific machine learning and neural operators; Bayesian learning and Gaussian process regression; and LLM and agentic AI workflows for process modeling, engineering knowledge integration, and domain fine-tuning.

I earned a Ph.D. in Computational Mechanics at the University of Illinois Urbana-Champaign, advised by Prof. Oscar Lopez-Pamies, and an M.S. in Computer Science focused on scientific machine learning and optimization, advised by Prof. Arindam Banerjee. I also hold an M.S. in Civil Engineering with a minor in Computational Science and Engineering from Illinois.

Before Illinois, I completed a B.Tech. in Civil Engineering at IIT Guwahati, where I received the Institute Silver Medal for ranking first in my graduating class.

Portrait of Bhavesh Shrimali

Research

From physical laws to intelligent engineering systems

I work where solid mechanics, applied mathematics, scientific computing, and modern AI reinforce one another— from high-fidelity simulation to uncertainty-aware surrogates and tool-using AI workflows.

Computational mechanics

  • High-performance finite elements. Parallel FEniCS/FEniCSx and PETSc solvers for nonlinear, multiphysics problems.
  • Abaqus fluency. Advanced nonlinear FEA in Abaqus, including constitutive-model implementation and custom user-subroutine workflows.
  • Macroscopic theories. Homogenization and variational methods for heterogeneous materials, finite deformation, viscoelasticity, and fracture.
  • Open-source software. Contributions to scikit-fem and Ferrite.jl.
FEniCS implementation Abaqus implementation

AI for engineering systems

  • LLMs and agentic AI. Tool-using workflows for process modeling, domain adaptation, and fine-tuning on engineering knowledge.
  • Bayesian learning and GPR. Uncertainty-aware surrogate models, probabilistic inference, and data-efficient prediction.
  • Scientific machine learning. Neural operators, PINNs, FNOs, and hybrid solvers that combine learned components with finite-element structure.
  • Optimization theory. Understanding how architecture and width shape gradient-descent behavior in DeepONets and Fourier neural operators.

Publications

Computational mechanics, multiphysics, and AI

Service & path

A research life across disciplines

Peer review

I have served as a referee for journals spanning mechanics, materials, and applied mathematics.

  • International Journal of Non-Linear Mechanics
  • Extreme Mechanics Letters
  • Journal of Applied Mechanics
  • Acta Mechanica
  • Journal of Thermal Stresses

Academic path

  1. University of Illinois logo
    University of Illinois Urbana-ChampaignM.S. Civil Engineering, Ph.D. Computational Mechanics, M.S. Computer Science · 2015–2023
  2. TU Braunschweig logo
    TU BraunschweigDAAD-WISE research intern · Summer 2014
  3. Hong Kong University of Science and Technology logo
    HKUSTResearch intern · Summer 2013
  4. IIT Guwahati logo
    IIT GuwahatiB.Tech. Civil Engineering, Institute Silver Medal · 2011–2015

News

Selected milestones

  1. Joined Micron Technology; now Senior Engineer, Advanced Modeling and AI Solutions.

  2. Started working at Kimberly-Clark as a Lead Scientist in the Virtual R&D team.

  3. Defended my thesis and graduated with a Ph.D. in Mechanics and an M.S. in Computer Science.

  4. Received the annual travel fellowship from the Structures group at Illinois.

Earlier news and teaching

  1. Ranked as an Outstanding TA for the second time.

  2. Presented “Homogenization of Porous Elastomers” at the SES 2019 minisymposium on soft materials. Slides

  3. Completed a semester as TA for the advanced graduate course Constitutive Modeling.

  4. Completed a second term as TA for Structural Mechanics and formally completed the Ph.D. coursework requirements.

  5. Completed a semester as TA for graduate Finite Element Methods, including teaching two lectures.

  6. Completed a semester as TA for Structural Mechanics and was ranked as an Outstanding TA.

  7. Graduated with an M.S. in Civil Engineering and a minor in Computational Science and Engineering.

  8. Completed a term as TA for CS 357: Numerical Methods, designing problem sets and autograded solutions.

  9. Delivered a three-hour hands-on workshop on using LaTeX in scientific writing.

  10. Completed two semesters as TA for CS 125, including office hours and Java programming assignments.

  11. Graduated from IIT Guwahati with the Institute Silver Medal and delivered the graduating speech.

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