Syed Muhammad Mujtaba

Syed Muhammad Mujtaba

Internee

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location of Syed Muhammad MujtabaAbu Dhabi Emirate, United Arab Emirates

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  • Timeline

  • About me

    Graduate Researcher at Khalifa University

  • Education

    • Universiti Teknologi PETRONAS

      2018 - 2020
      MSc. in Mechanical Engineering ENGINEERING
    • Khalifa University

      2023 - 2026
      Doctor of Philosophy - PhD Mechanical and Nuclear Engineering
    • NED University of Engineering and Technology

      2013 - 2017
      Bachelor’s Degree Industrial and Manufacturing Engineering

      Completed my B.E. in Industrial and Manufacturing from NEDUET in January 2017.

  • Experience

    • EBM

      Jun 2015 - Jul 2015
      Internee

      A month internship at English Biscuits Manufacturers in Production Department. I learned how the production improvements techniques can be implemented at industry. I Worked as a part of TQM (Total Quality Management) team, specifically on ECRS technique (to reduce change over time), experience to conduct time and motion study and identify the kaizens. This experience improves my data analysis skills.

    • Learning Pitch

      Jan 2017 - Dec 2017
      Teacher

      Served as a vibrant team member of the first online learning management system of Pakistan named “Learning Pitch”. Delivered physics lectures, trained new teachers for lecture recordings and engineered a light board.

    • Artistic Fabric Mills

      Apr 2017 - Aug 2017
      Management Trainee

      Experienced as a management trainee in the maintenance department of a textile industry. My core responsibilities were to generate the issue permit to collect spare parts from utility department, document mechanical maintenance activities. Additionally, I was engaged with a team responsible for the erection of fabric washing machine.

    • Universiti Teknologi PETRONAS

      Jan 2018 - Aug 2020
      Postgraduate Researcher

      Thesis: Adaptive Threshold Based Leak Detection System for Gas Mixture PipelinesIn the first part, a 150 km natural gas pipeline model was simulated using laws of mechanics and thermodynamics. Model was also validated using OLGA dynamic simulator and experimental data from literature. In the other part, simulation data were used for system model identification using learning parameters. Adaptive thresholding technique was implemented to successfully detect 2% leak under transient boundary conditions. Show less

    • Pakistan Petroleum Limited

      Feb 2021 - Feb 2021
      Internee at Design and Technical Service Department

      Developed a basic understanding of the design of mechanical components in gas processing plant using international standards and codes. Hands-on experience to evaluate, analyze, and calculate the thickness of pipelines and pressure vessels using ASME B31.3 and section VIII division 01. I am also familiar with the basics of Caesar II for sustained and thermal analysis.

    • Universiti Teknologi PETRONAS

      May 2021 - Nov 2022
      Research Scientist

      Conduct research on advanced fault detection and diagnostic systems for oil and gas pipelines, with an emphasis on creating robust, autonomous leak detection technologies capable of operating under dynamic, real-world conditions. Utilizing the OLGA multiphase simulator, generate transient data for model training, validation, and testing, and employ advanced techniques such as non-linear regression and artificial neural networks in MATLAB to enhance leak detection accuracy. Additionally, mentor graduate students, prepare research proposals, and present findings to secure funding, contributing to the advancement of innovative solutions in pipeline safety and energy security. Show less

    • Khalifa University

      Jan 2023 - now
      Postgraduate Researcher

      Synthesize advanced materials to enhance both ionic conductivity and mechanical strength using techniques such as solvent casting, sol-gel processing, vacuum filtration, pelletization, and ultrafast sintering. Characterize these materials through methods like X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Raman Spectroscopy, FTIR, TGA, contact angle measurements, and XPS to evaluate their structural, chemical, and surface properties. To assess ionic conductivity, conduct Electrochemical Impedance Spectroscopy (EIS). Perform mechanical tests, including compression and toughness assessments, to evaluate their strength and durability. Show less

  • Licenses & Certifications

    • Deep Learning with MATLAB

      TechSource Systems
      Dec 2021
    • Verified International Academic Qualifications

      World Education Services
      Jan 2021
      View certificate certificate