Mitra Sedeeqi

Background

About Mitra Sedeeqi

Computational physicist with a PhD in Applied Physics from SUNY Binghamton (2025), specializing in atomistic modeling, molecular dynamics (LAMMPS), and machine learning for materials design. Research centers on thermal transport in nanostructured and disordered solids, with applications in semiconductors, thermoelectrics, and energy storage systems. Key contributions include- Development of GPU-accelerated molecular dynamics pipelines (LAMMPS–Python) for large-scale simulations on HPC clusters- Advanced methods for extracting phonon lifetimes, heat transport coefficients, and thermal conductivity using Monte Carlo, VACF, and spectral energy density analysis- Integration of machine learning frameworks (PyTorch, TensorFlow) to predict structure–property relationships and accelerate materials optimization- Publications and manuscripts addressing thermal transport in semiconductor nanostructures, porous media, and nanocomposites. Recognized for strong problem-solving ability, technical independence, and research rigor, with a commitment to advancing the predictive design of semiconductors and thermoelectric materials for energy storage applications. Passionate about accelerating scientific discovery through AI and computational methods, with a proven ability to drive innovative research directions independently.