Sense
Sensors, circuits, and embedded hardware gather the real-world signal.
Portfolio '26
Designing intelligent solutions through embedded systems, machine learning, electronics, software, and robotics-focused innovation.
"The strongest steel is forged in the hottest fire."
About Me
I am an Electrical Engineering student at NUST, passionate about building intelligent systems that blend hardware, software, and innovation. My interests span embedded systems, robotics, autonomous systems, machine learning, and computer vision, with a focus on creating technologies that are practical, impactful, and future-driven.
Sensors, circuits, and embedded hardware gather the real-world signal.
C++, Python, and machine-learning logic turn raw inputs into decisions.
The final system is designed to be practical, reliable, and easy to understand.
technical projects across embedded systems, ML, software, electronics, and web development.
position at Voltfest Embedded Systems Competition for a POV display project.
Skills
The tools and technologies I use to turn ideas into functional systems.
C++, Python, Object-Oriented Programming, Data Structures, File Handling, Algorithmic Logic, Debugging.
Website development, responsive UI design, web applications.
Arduino UNO, ESP-12, Bluetooth modules, motor drivers, sensors, LDR, laser sensing, Hall-effect sensors.
Supervised learning, classification, data preprocessing, feature extraction, model evaluation, NLP fundamentals.
LTspice, analog circuit design, signal conditioning, waveform analysis, filtering, circuit simulation.
Figma, Canva, digital design.
Robotics, autonomous systems, drone technology, embedded systems, and computer vision.
Technical writing, client communication, project management, teamwork, problem solving.
Projects
A collection of engineering projects built across software, embedded systems, machine learning, and electronics.
C++ • OOP • System Simulation
A city-scale EV charging ecosystem designed to optimize dock allocation, scheduling, renewable energy usage, and charging efficiency.
Built with scalable object-oriented architecture and real-world operational logic.
Python • Machine Learning • NLP
A supervised machine learning pipeline for detecting spam emails using text preprocessing, feature extraction, and classification.
Designed to transform unstructured text into accurate predictive insights.
Deep Learning • CNN • TensorFlow
A handwritten digit recognition system trained on the MNIST dataset using deep learning techniques for image classification.
Demonstrates real-world computer vision through high-accuracy handwritten digit recognition.
Python • Machine Learning • Data Analytics
A machine learning model that predicts California housing prices using feature selection, regression, and data preprocessing.
Built with Random Forest regression and optimized using feature importance analysis.
Python • KNN • Machine Learning
A flower species classification model using the Iris dataset with feature scaling and K-Nearest Neighbors.
Demonstrates supervised learning through accurate multi-class classification.
ESP-12 • Embedded Systems • IoT
A rotating LED display that creates stable 360-degree visual patterns using precise timing and Hall-effect synchronization.
Awarded 3rd Position at Voltfest 2026 among 26 competing teams.
Analog Electronics • Filter Design • Signal Processing
Designed, simulated, and validated analog filter circuits for waveform extraction using Fourier analysis, LTspice simulations, and practical hardware implementation.
Implemented four analog filter stages for waveform extraction and signal conditioning.
C++ • OOP • Data Structures
A parking management simulation featuring intelligent slot allocation, billing automation, monitoring, and transaction management.
Designed to simplify parking operations through efficient data management algorithms.
Analog Circuits • Electronics • Simulation
An analog thermal safety controller using operational amplifiers and comparator-based decision logic for real-time protection.
Validated through both LTspice simulation and hardware implementation.
Python • Data Analysis • Machine Learning
An energy management platform for monitoring consumption, automating billing, and forecasting future energy usage.
Integrated predictive analytics using linear regression for smarter energy planning.
Arduino • Embedded Systems • Robotics
A wireless robotic vehicle featuring Bluetooth communication, PWM motor control, and real-time navigation.
Built to demonstrate reliable hardware-software integration and embedded control.
Arduino • Embedded Systems • Sensors
A laser-based intrusion detection system using LDR sensing and real-time alarm activation for security applications.
Combined embedded electronics with practical system design for reliable intrusion detection.
Experience
Practical growth through internships, freelance projects, and hands-on technical work.
Education
Building a strong foundation in electrical engineering, electronics, programming, and intelligent systems.
Recognition • Certifications • Achievements
Secured 3rd Position among 26 competing teams for developing a Persistence of Vision (POV) Display, showcasing innovation in embedded systems, IoT, and real-time hardware integration.
Awards
Recognition • Certifications • Achievements
CEME, NUST
Secured 3rd Position among 26 teams for developing a POV Display.
Coursera
Certification
Coursera
Python Certification
RAC, NUST
Hands-on robotics workshop
IBM
Certification
CMC, BRISC & BURAQ
Workshop
Recognition • Certifications • Achievements
CEME, NUST
Secured 3rd Position among 26 teams for developing a POV Display.
Coursera
Certification
CMC, BRISC & BURAQ
Workshop
Coursera
Python Certification
RAC, NUST
Hands-on robotics workshop
IBM
Certification
Collaborate
Passionate about building intelligent technologies at the intersection of robotics, machine learning, computer vision, and autonomous systems.
Designing intelligent systems that combine hardware, software, and automation to solve real-world challenges.
Developing intelligent models that transform data into meaningful insights and informed decisions.
Exploring how machines can perceive, interpret, and interact with the world through visual intelligence.
Building systems capable of sensing, adapting, and operating intelligently with minimal human intervention.
Open to internships, research opportunities, engineering projects, startups, and meaningful collaborations.
A few places where I share, create, and connect.
Have an opportunity, project, collaboration, or idea in mind? Feel free to reach out.