Muhammad Usman Khawar

Academic

Career

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Muhammad Usman Khawar
Cell: +923190231205 |  Email: usman6670167@gmail.com
LinkedIn: https://www.linkedin.com/in/muhammad-usman-khawar-04a37328a/
Address: VILLAGE AND PO. CHOPALA , Gujrat , Pakistan
PROFESSIONAL PROFILE
Detail-oriented Electrical Engineering student with strong practical exposure to industrial electrical systems, automation, and motor
control. Hands-on experience in PLC-based automation, VFD configuration, power quality analysis, and electrical panel testing
gained through an industrial internship at a large manufacturing facility. Familiar with industrial safety standards, troubleshooting, and
reading electrical schematics. Motivated to contribute to power, automation, or maintenance roles while continuously enhancing
technical and problem-solving skills in a professional engineering environment.
EDUCATION
Bachelors of Electrical Engineering
School of Electrical Engineering and Computer Science , Islamabad (2026)
INTERNSHIP EXPERIENCE
Service Industries Gujrat
13-Jun-2025 - 09-Aug-2025
Completed an 8-week internship in the Instrumentation & Electrical Department at Servis Tyres Pvt. Ltd. Gained hands-on
experience with PLC-based automation, VFD configuration, power quality analysis, and industrial motor control (DOL & Star-Delta).
Assisted in electrical panel testing, TBM troubleshooting, inverter installation, and fault diagnosis while following industrial safety
standards and collaborating with multidisciplinary engineering teams.
FINAL YEAR PROJECT
AI based Smart Power Management System ( Residential )
Proposed an AI-enabled IoT-based residential power management system aimed at reducing electricity costs and improving
appliance safety. The system is planned to provide real-time, room-level energy monitoring through non-invasive current sensors and
a central control hub installed at the main distribution board. It is intended to support automated over-voltage, under-voltage, and
overload protection with remote power control. A cross-platform mobile application is planned for real-time visualization, historical
analytics, and user-defined thresholds. The project also proposes on-device machine learning using TensorFlow Lite for offline
electricity bill forecasting and energy optimization.
TECHNICAL EXPERTISE
Electrical Maintenance & Troubleshooting
Basic hands-on experience in identifying, testing, and troubleshooting electrical faults in industrial equipment, motor circuits, and
control panels while following safety procedures.
Motor Control Systems
Familiar with DOL and Star-Delta motor starters, contactors, overload relays, and timers. Able to understand wiring diagrams and
assist in motor control circuit testing.
PLC & Industrial Automation Basics
Basic exposure to PLC-based automation, ladder logic understanding, I/O modules, and monitoring automated processes in a
manufacturing environment.
Variable Frequency Drives (VFDs)

AI enrichment