About​

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I’m a computational materials scientist who builds atomistic and machine-learning models to understand how fluids and materials behave at the nanoscale.

I use physics-based modeling to study the phase equilibria, transport, and adsorption of fluids in confined systems where bulk thermodynamics breaks down. I also investigate the thermal transport and mechanical properties of 2D materials, identifying the mechanisms behind these behaviors and predicting how they change across varying conditions.

My toolkit spans molecular dynamics, Monte Carlo, DFT (VASP, Quantum ESPRESSO), and machine learning (including MLIPs). I run large-scale simulations on HPC clusters utilizing Python-automated workflows.

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Technical Skills​

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Computational Methods:

Molecular Dynamics (MD), Monte Carlo (MC), Density Functional Theory (DFT), Physics Based Modeling, Machine Learning Interatomic Potentials (MLIPs), Multiscale Modeling

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Software and Tools:

OVITO  Abaqus  COMSOL  Solid Works  Microsoft Office​

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Programming & Data Science:

Python, MATLAB, Bash, LaTeX

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Education

• ​Ph.D. in Mechanical Engineering in 2026 
  University at Buffalo, Buffalo, NY, USA

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• Master of Science in Mechanical Engineering (Energy Conversion) in 2020

       Imam Khomeini International University (IKIU), Qazvin, Iran

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• Bachelor of Science in Mechanical Engineering in 2017

       Khajeh Nasir Toosi University of Technology (KNTU), Tehran, Iran