Akash Dhruv
Assistant Computational Scientist
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolAkash Dhruv is an Assistant Computational Scientist with 12 years of experience applying software design, algorithm development, DevOps, and performance engineering to scale complex scientific computing applications. Based at Argonne National Laboratory, he develops performance-portable software and explores applications of large language models to accelerate simulations in multiphase fluid dynamics, weather forecasting, and high-energy physics. His background includes designing high-fidelity multiphase flow solvers, hybrid parallelization strategies for multicore architectures, and integrating numerical simulation workflows with machine learning for predictive science. He has a PhD in Mechanical and Aerospace Engineering and a track record of contributing to open-source simulation infrastructure and AMR libraries for exascale computing. Colleagues rely on him to bridge deep domain physics with practical software engineering—balancing reproducibility, testing, and performance at scale. Notably, he brings hands-on UAV control and morphing-wing design experience that informs creative, cross-disciplinary solutions to simulation and control problems.
12 years of coding experience
4 years of employment as a software developer
Bachelor of Technology (B.Tech.) Mechanical Engineering, Bachelor of Technology (B.Tech.) Mechanical Engineering at National Institute of Technology SuratDoctor of Philosophy - PhD Mechanical and Aerospace Engineering, Doctor of Philosophy - PhD Mechanical and Aerospace Engineering at The George Washington University
Github Skills (35)
energy9
cluster-computing9
amr9
scientific-computing8
snl-applications8
parallel-computing8
openmp8
journal8
mpi7
hpc7
forecasting7
petsc7
multiphysics7
python7
open-access7
Programming languages (8)
Github contributions (5)
akashdhruv/FlowX
Feb 2019 - Dec 2022
Contributions:5 releases, 297 commits, 34 PRs in 3 years 10 months
Box-Tools/BoxKit
Jun 2021 - Jan 2023
A Python library to manage analysis of block-structured simulation datasets.
Contributions:4 releases, 586 commits, 261 PRs in 1 year 7 months
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