About Achref GADHGADHI

  • Academic Level  Master’s Degree
  • Age  33 - 37 Years
  • Salary  2567
  • Gender  Male
  • Nationality  Tunisie
  • Position  Research and Development
  • Others Sector 

    Energy, Photovoltaic systems, Electric Mobility, AI, Robotics, Telecommunication.

  • Viewed 12
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About me

PhD candidate at the National School of Engineers of Carthage (ENICarthage), University of Carthage, specializing in autonomous robotics, RSSI-based localization, AI-driven indoor positioning,
and path planning in indoor environments. My research primarily focuses on autonomous robotics,
specifically addressing localization and path planning challenges. In addition to my robotics and AI expertise, I have a solid background in electrical mobility and renewable energy. I worked as an instructor in Electricity and EVSE installation, and I developed a Master’s project on “Design and Modeling of a Traction System for Electric Vehicles”. I also have strong knowledge of photovoltaic systems and am proficient in PVsyst software for solar energy simulation and analysis.

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Education

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Experience

  • 2022 - 2025
    Bootcamp Training Center

    Electricity & EVSE Installation Instructor

    worked as a full-time instructor specializing in Building Electricity and EVSE installation and
    setup from 2022 to 2024. My role involved teaching the fundamentals of electrical domestic installation,
    guiding trainees through practical applications, and ensuring they acquired the necessary
    skills to meet industry standards. I focused on safety, efficiency, and the latest advancements in
    electrical systems, preparing professionals for real-world installations and emerging technologies in
    electric vehicle charging infrastructure.

  • 2019 - 2022
    Research Lab SE&ICT, University of Carthage

    Research assisstant

    • Researching Autonomous Robotics under [Y. Hachaichi & H. Zairi]
    • Key Contributions: worked on RSSI-based localization techniques for autonomous robotics, enhancing
    the accuracy of indoor positioning in complex environments using machine learning algorithms.

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Languages

Arabic
Proficient
Frensh
Intermediate
English
Intermediate
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