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Muhammad Ibrahim

NUST · 2026

muhammad.ibrahim9730@gmail.com

Phone

923185070544

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GitHub

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Academic

Program

Bachelors of Engineering in Electrical Engineering

CGPA

3.23

Year

2026

Education

School of Electrical Engineering and Computer Sciences (SEECS)

Address

Village and Post Office Maira Mohra , Tehsil and District Rawalpindi , Rawalpindi , Pakistan

DOB

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Career

Current role

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Target role

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Skills

C, C++, Python, Verilog, YOLOv8, OpenCV, PyTorch, TensorFlow, DeepSORT, Scikit-learn, MATLAB, Simulink, Proteus, PSPICE, Quartus, ModelSim, MATLAB DSP Toolbox, ESP32, STM32, Arduino, FPGA, ATmega16, UART/SPI/I2C, LabVIEW, Arduino IDE, Blynk, AutoCAD, Google Colab, MS Office, Computer Vision, Embedded Systems, Machine Learning

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.

Muhammad Ibrahim
Cell: 923185070544 |  Email: muhammad.ibrahim9730@gmail.com
Address: Village and Post Office Maira Mohra , Tehsil and District Rawalpindi , Rawalpindi , Pakistan
PROFESSIONAL PROFILE
Final-year Electrical Engineering student at NUST with practical experience in computer vision, embedded systems, and machine
learning. Specialized in building real-time drone and IoT solutions, with a strong focus on deploying intelligent models on embedded
hardware for reliable, real-world systems.
EDUCATION
Bachelors of Engineering in Electrical Engineering
School of Electrical Engineering and Computer Sciences (SEECS) , NUST , H12 , Islamabad , 3.23 (4)
INTERNSHIP EXPERIENCE
National Aerospace Science & Technology Park (NASTP)
25-Jul-2025 - 25-Aug-2025
Computer Vision & Web App Development Intern -Developed a computer vision–based business card digitization system for
automated text extraction and Excel export. -Contributed to backend development of a seller-side e-commerce web application for
product and order management.
DroNext Pvt. Ltd., Graduate Research Complex, SEECS NUST
10-Jun-2025 - 23-Jan-2026
Computer Vision Intern -Worked on the computer vision module of a vision-guided autonomous drone project. -Implemented YOLO-
based object detection for real-time target detection and tracking.
FINAL YEAR PROJECT
Taak: Vision-Guided Laser Tracking System for Autonomous Drone Missions
Developing an intelligent autonomous drone system leveraging computer vision and machine learning for real-time multi-class object
detection, tracking, and re-identiﬁcation. The drone is capable of autonomous navigation and adaptive target tracking, integrating
flight control with coordinated, deployable ML models to maintain robust multi-object tracking in dynamic environments.
TECHNICAL EXPERTISE
Programming:
C, C++, Python, Verilog
Machine Learning & Computer Vision:
OLOv8, OpenCV, PyTorch, TensorFlow, DeepSORT, Scikit-learn
Simulation & Design:
MATLAB, Simulink, Proteus, PSPICE, Quartus, ModelSim, MATLAB DSP Toolbox
Embedded Systems & Hardware:
ESP32, STM32, Arduino, FPGA, ATmega16, UART/SPI/I2C
Software Tools & IDEs:
LabVIEW, Arduino IDE, Blynk, AutoCAD, Google Colab, MS Office

AI enrichment

Muhammad Ibrahim is a final-year Electrical Engineering student at NUST with a focus on computer vision, embedded systems, and machine learning. He has internship experience in developing computer vision applications and autonomous drone tracking systems using technologies like YOLO and OpenCV.

Skills (AI)

["Computer Vision", "Machine Learning", "Embedded Systems", "Python", "C++", "YOLO", "OpenCV", "PyTorch", "TensorFlow", "Drone Development", "IoT", "C", "Verilog", "MATLAB", "STM32", "ESP32", "FPGA"]

Status: ai_done

Provenance

Source file: SEECS - Electrical Engineering-2026.pdf
From job #259 page 68
Created: 1778168427