Muhammad Ibrar - Electrical Engineering Portfolio

Following are my Area of Research Interest

Intrigued by the possibilities of embedded systems and automation.

Keen on leveraging sensing , power electronics, IoT, and Wireless Sensor Networks.

Delivered IoT training sessions on sensor interfacing, cloud integration, and data analytics using the Keysight U3810A IoT Teaching Kit, enhancing students’ practical skills in network protocols (e.g., UART, I2C, SPI,MQTT) and IoT communication techniques..
Guided students through programming, testing, and troubleshooting and integrating microcontrollers like BeagleBone with various IoT communication technologies, including Zigbee, Bluetooth LE, and MQTT, optimizing data transmission efficiency and system power consumption.
Provided guidance on network protocol implementation, teaching students how to establish secure and efficient data flows between devices

Led and executed over 30 lab sessions on material testing (tensile testing, stress-strain analysis, Rockwell hardness, and column buckling) for students, providing hands-on training in experimental procedures, enhancing their application of engineering principles to real-world problems.
Provided technical guidance and troubleshooting support on analyzing material behavior and results, improving proce.

Designed and delivered sensor-driven IoT embedded solutions, customizing hardware, software, and cloud integration to meet client requirements, with a focus on real-time monitoring.
Programmed microcontrollers using Embedded C and Python to develop embedded systems for real-time telemetry, performance diagnostics, and system efficiency optimization.
Conducted post-deployment system maintenance, troubleshooting, and error resolution for IoT-enabled embedded systems, ensuring ongoing system stability.
Mentored junior engineers and technicians, promoting collaboration in system troubleshooting and optimization and representing the lab on national level.

Tested and debugged embedded software and firmware to ensure system reliability, performance, and energy efficiency, utilizing diagnostic tools to validate system performance.
Implemented emerging IoT technologies to enhance system functionality for real-time energy monitoring and diagnostics of solar panels.
Implemented IoT technologies and integrated emerging trends into development strategies to enhance system connectivity, data flow, and overall functionality.
Designed PCBs using CAD software.

Assisted the professor in grading assignments and updating learning materials.
Helped resolve student problems using the Think-Pair-Share strategy to enhance the learning experience.
Performed simulations and laboratory experiments to facilitate students in the lab.
Wrote technical reports under the supervision of the professor.

Developed lab exercises for undergraduate Engineering students focused on edge AI, cloud analytics, and IoT integration, enhancing hands-on STEM education for real-world applicability and reducing lab setup issues by 30%.
Tested and implemented 11 IoT-based lab modules integrating analog & digital circuits, power electronics, embedded hardware, and sensors for hands-on undergraduate experimentation.

Developing lightweight edge AI models and embedded sensor systems to classify solar panel defects in real time, enabling reliable, low-power monitoring for improved renewable energy efficiency.