Hasan Gharaghani Pour | application of radiation | Best Researcher Award

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Mr. Hasan Gharaghani Pour| application of radiation | Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Hasan Gharaghani Pour is a skilled programmer with 10 years of project-oriented experience, working as a freelancer with diverse clients. He is proficient in various programming languages including Matlab, Mathematica, Fortran, and .NET VB. His expertise extends to nuclear programming, Windows application development, and utilizing various numerical methods for linear and non-linear optimization, particularly for calibrating devices. Hasan is adept at artificial neural networks and possesses a creative flair for problem-solving. He has a complete mastery of Internet search and the Microsoft Office suite, especially PowerPoint, with partial mastery of Photoshop. Hasan is an excellent communicator with proficiency in English.

šŸŒ Professional Profiles

Education:

Ph.D. in Nuclear Physics Institute/University: Shahrood University of Technology, Shahrud, Semnan, Iran Duration: 2018 – Present GPA: 17.18

Projects:

Calibration program for nuclear devices for Parto Tehzih Besat, providing smooth behavior using a degree 3 function. Writing several thousand Fortran programs for internet-based applications, including numerical calculations, solving differential equations, and root finding. Developing dozens of programs under Windows with VB.NET for various purposes including device calibration, dose calculation, and physics laboratory simulations.

šŸ“šTop Noted Publication

      • Evaluation of nuclear data analysis techniques for volume fraction prediction in the flow meter.
        • Publisher: Radiochimica Acta, October 2022
        • Link

     

      • A new approach to calculating the ratio of the Compton to total mass attenuation coefficient.
        • Publisher: Radiation Physics and Chemistry, July 2023
        • Link

     

      • Analytical modeling of the neutron response function of the NE213 organic liquid scintillator in the energy range of 0.2 MeV to 148 MeV.
        • Publisher: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, April 2021
        • Link

     

      • A novel approach to accelerate training in artificial neural networks to detect three-phase flows using a gamma source and a detector.
        • Publisher: Radiation Physics and Chemistry, March 2024
        • Link