Faculty Img
  • Phone:

    0535094410

  • Email:

    mkhan1@pmu.edu.sa

  • Office No:

    F046

  • Muhammad Ijaz Khan

  • Job Title :

    Assistant Professor

  • College :

    College of Engineering


  • Department :

    Mechanical Engineering


Dr. Muhammad Ijaz Khan (MIKHAN) is an Assistant Professor at Prince Mohammad Bin Fahd University, KSA. He holds a Ph.D. in Fluid Mechanics from Quaid-I-Azam University, Islamabad, Pakistan, and has completed a postdoctoral fellowship in Energy at Peking University, China, a globally recognized institution ranked among the top 10 universities worldwide.

Dr. MIKHAN’s research expertise encompasses applied mathematics, fluid mechanics, computational fluid dynamics (CFD), and optimization strategies for renewable energy applications. His work is particularly focused on Latent Heat Thermal Energy Storage (LHTES), employing nano-enhanced phase change materials (Nano-PCMs) and hybrid nanofluids to improve energy efficiency and sustainability. Additionally, his research integrates nanotechnology, entropy analysis, and heat transfer to advance thermal management systems.

Throughout his academic career, Dr. MIKHAN has held research and teaching positions in Pakistan, China, Saudi Arabia, the United States (American University of New York – Lebanon Campus), and India. His appointments include:

  • Assistant Professor (Pakistan, 2020–2024)
  • Research Associate (China, 2021–2023)
  • Adjunct Professor (Saudi Arabia, 2020–2023)
  • Adjunct Professor (American University of New York – Lebanon Campus, 2021–2024)

Dr. MIKHAN has led and contributed to several high-impact international research projects, securing prestigious funding awards, including the High Talent International Researchers Fund and the Young Foreign Expert Project Fund from the Ministry of Science and Technology of China.

Recognized among the top 2% of researchers globally (Stanford University, USA), Dr. MIKHAN has an H-index of 105 and 41,000 total citations, reflecting the significant influence of his scholarly contributions.

His expertise extends to AI-based modeling, machine learning-driven optimization, and multi-scale energy simulations, with proficiency in Mathematica, COMSOL Multiphysics, MATLAB Simulink, and other advanced computational tools.