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  1. The role of 3D electrostatic field in modeling the electrospinning process

    Article • Journal of Applied Physics, January 2024, American Institute of Physics

    Sk. Mashfiqur Rahman

  2. Physics‐based deep neural network model to guide electrospinning polyurethane fibers

    Article • Journal of Applied Polymer Science, September 2022, Wiley

    Sk. Mashfiqur Rahman

  3. Memory embedded non-intrusive reduced order modeling of non-ergodic flows

    Article • Physics of Fluids, December 2019, American Institute of Physics

    Professor Ionel Michael Navon, Sk. Mashfiqur Rahman, Shady Ahmed

  4. Nonintrusive reduced order modeling framework for quasigeostrophic turbulence

    Article • November 2019, American Physical Society (APS)

    Sk. Mashfiqur Rahman

  5. A deep learning enabler for nonintrusive reduced order modeling of fluid flows

    Article • Physics of Fluids, August 2019, American Institute of Physics

    Sk. Mashfiqur Rahman, Suraj Pawar

  6. A Relaxation Filtering Approach for Two-Dimensional Rayleigh–Taylor Instability-Induced Flows

    Article • Fluids, April 2019, MDPI AG

    Sk. Mashfiqur Rahman

  7. A dynamic closure modeling framework for model order reduction of geophysical flows

    Article • Physics of Fluids, April 2019, American Institute of Physics

    Sk. Mashfiqur Rahman, Shady Ahmed

  8. A Hybrid Approach for Model Order Reduction of Barotropic Quasi-Geostrophic Turbulence

    Article • Fluids, October 2018, MDPI AG

    Sk. Mashfiqur Rahman

  9. A localised dynamic closure model for Euler turbulence

    Article • International Journal of Computational Fluid Dynamics, October 2018, Taylor & Francis

    Sk. Mashfiqur Rahman

  10. A Hybrid Analytics Paradigm Combining Physics-Based Modeling and Data-Driven Modeling to Accelerate Incompressible Flow Solvers

    Article • Fluids, July 2018, MDPI AG

    Sk. Mashfiqur Rahman