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Hafiz Muhammad Ahmed Safdar

NUST · 2026
Email
ahmedsafdar3@gmail.com
Phone
923318446696
LinkedIn
https://www.linkedin.com/in/hafiz-muhammad-ahmed-safdar-50a3aa369/
GitHub

Academic

Program
Bachelors in Electrical Engineering
CGPA
Year
2026
Education
SEECS
Address
Lahore, Pakistan
DOB

Career

Current role
Target role
Skills
Embedded Systems, Control Systems, Motor Drive Applications, MATLAB/Simulink, Machine Learning, Computer Vision, Microcontroller-based System Design, Automation, Data-driven Problem Solving, Sliding Mode Control, STM32, Arduino, Embedded C, GPIO Control, Relay Interfacing, DC Motor Speed Control, Robotic Arm, Python, Image Processing, Edge Detection, Object Recognition, Deep Learning, Object Detection, Edge Computing, NVIDIA Jetson Nano

Verbatim text

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Hafiz Muhammad Ahmed Safdar
Cell: 923318446696 |  Email: ahmedsafdar3@gmail.com
LinkedIn: https://www.linkedin.com/in/hafiz-muhammad-ahmed-safdar-50a3aa369/
Address: 25-B ALPHA COOPERATIVE HOUSING SOCIETY , Lahore , Pakistan
PROFESSIONAL PROFILE
Electrical Engineering undergraduate at NUST with hands on experience in embedded systems, control and motor drive applications,
MATLAB/Simulink modeling, and interdisciplinary projects in machine learning and computer vision. Skilled in microcontroller-based
system design, automation, and data-driven problem solving, with research exposure to sliding mode control. Seeking to apply strong
analytical and practical skills in challenging engineering roles.
EDUCATION
bachelors in electrical engineering
seecs , Lahore , 2.3 (2026)
INTERNSHIP EXPERIENCE
Graduate Research Complex
16-Jun-2025 - 05-Sep-2025
Wrote a Research Paper on Bone Cancer Treament using Sliding Mode Control
FINAL YEAR PROJECT
OLIVE YIELD DETECTION USING COMPUTER VISION AND EDGE COMPUTING
This final year project focuses on olive yield detection using computer vision and edge computing to provide an efficient, accurate,
and real-time solution for olive production estimation. The system uses image data captured from cameras or mobile devices to
automatically detect and count olives on trees using computer vision techniques such as image processing and deep learning based
object detection. To ensure low latency, reduced bandwidth usage, and on-site processing, the model is deployed on an edge
computing device ( NVIDIA Jetson Nano ). This approach helps farmers and agricultural planners estimate yield early, optimize
harvesting strategies, reduce labor costs, and support data-driven decision-making in precision agriculture.
TECHNICAL EXPERTISE
Embedded Systems and MicroControllers
STM32 microcontroller programming Arduino-based system design Embedded C programming GPIO control, relay interfacing Real-
time control of hardware systems
Control Systems And Motor Control
Research Paper on Bone Cancer Treatment using SMC ( Sliding mode Control ). ( Under Review ) DC motor speed control Robotic
Arm using Servo Motors
Machine Learning & Python
Salary Prediction Model - Predicting Salary based on the persons job title, location, remote or on-site - by using Python Dog Breed
Identification - Predicting a Dog's Breed by putting photographs in it of different dogs - by using Python on Google Colab
Computer Vision
White Board Digitizer - image processing, edge detection, object recognition Dog Breed Identification - using Machine learning and
Computer vision to detect the breedof Dog.

AI enrichment

Electrical Engineering undergraduate at NUST with a focus on embedded systems, control theory, and computer vision. Demonstrates practical experience through academic projects involving edge computing, microcontroller programming, and machine learning applications.
Skills (AI)
["Embedded Systems", "Microcontrollers", "STM32", "Arduino", "Embedded C", "Control Systems", "Sliding Mode Control", "Motor Control", "Python", "Machine Learning", "Computer Vision", "Image Processing", "Edge Computing", "NVIDIA Jetson Nano", "MATLAB/Simulink"]
Status: ai_done
Provenance
Source file: SEECS - Electrical Engineering-2026.pdf
From job #259 page 173
Created: 1778168427