Nijat Rustamov

Physics, Math and Computing

PhD Candidate specializing in CFD, Physics-Informed Machine Learning, and parallel computing.

View My Work
About Me

I am a researcher bridging the gap between nano and macroscale fluid dynamics using modern high-performance computing. My work focuses on developing high-fidelity Computational Fluid Dynamics (CFD) solvers and accelerating them using Physics-Informed Neural Networks (PINNs).


Currently pursuing my PhD, I enjoy tackling complex multi-scale problems where fluid dynamics meets data science.

Profile Picture
Featured Projects

Introducing Marlin, a high-performance CFD Solver

A highly scalable Lattice Boltzmann Fluid Solver implemented in C++ with MPI.

C++ MPI GPU
FHKN Architecture

FHKN: Fourier-Hermite Kinetic Network

A sequence-to-state surrogate that maps early LBM transients to steady-state gas transport in nanoporous media — bypassing up to 300,000 solver iterations.

Python PyTorch GPU
PODMM Results

Multifidelity POD Surrogate

Proper Orthogonal Decomposition Mapping Method for coarse-to-fine resolution prediction of rarefied gas transport — 8× speedup over full LBM.

Python POD LBM
Wyoming CBG Population Map

WyoPop: Rural Mobility Prediction

Spectral Graph Neural Network predicting population inflow and outflow across Wyoming's 410 Census Block Groups over a 2-year recursive horizon.

Python GNN FFT
Publications

Books

Lingfu, L., Rustamov, N. and Aryana, S.A. (2026)
'Scale translation in complex porous media'
De Gruyter. In Progress

Journal Publications

Rustamov, N., Mostaghimi, P. and Aryana, S.A. (2025)
'On multi-block lattice Boltzmann method for high Knudsen number flows'
Advances in Geo-Energy Research, 16(2), pp. 143–157.
Rustamov, N., Liu, L. and Aryana, S.A. (2023)
'Scalable simulation of coupled adsorption and transport of methane in confined complex porous media with density preconditioning'
Gas Science and Engineering, 119, p. 205131.
Rustamov, N., Douglas, C.C. and Aryana, S.A. (2022)
'Scalable simulation of pressure gradient-driven transport of rarefied gases in complex permeable media using lattice Boltzmann method'
Fluids, 8(1), p. 1.
Kitterman, A., Rustamov, N., Liu, Y. and Aryana, S.A. (2026)
'Application of multifidelity proper orthogonal decomposition-based surrogate models to rarefied gas dynamics'
Physics of Fluids. Published  ·  doi: 10.1063/5.0333761

Under Review / In Press

Rustamov, N. and Aryana, S.A. (2026)
'Fourier-Hermite kinetic network for gas transport under high Knudsen numbers'
InterPore Journal. Under Review
Rustamov, N. and Xu, C. (2026)
'Rural population mobility prediction using dynamic graph neural networks: a Wyoming case study'
Engineering Applications of Artificial Intelligence. Under Review  ·  SSRN Preprint
Technical Stack

Computing & Languages

  • C/C++
  • Python
  • CUDA
  • MATLAB
  • HTML/CSS/JAVASCRIPT

HPC & Tools

  • MPI & OpenMP
  • Slurm / PBS
  • Docker
  • Git / CI/CD
  • CMake

CFD & ML

  • MOOSE
  • Ansys Fluent
  • PyTorch / TensorFlow
  • scikit-learn / SciPy
  • Paraview

AI Workflow

  • Agentic Development
  • Prompt Engineering
  • LLM APIs (Claude / GPT)
  • Vibe Coding