Electrical Engineering: Recent submissions

  • Design of Switch Filter Bank 
    Project Supervisor DR. ZUBAIR AHMED, Hammad Saboor Muhammad Talha Waleed Zafar (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    In this project, we worked on the design of a two channel a Switch Filter Bank which is a crucial component in communication systems. It consist of two parallel coupled line microstrip filters having center frequency of ...
  • NEAR REAL-TIME SPECTRUM ANALYZER 
    Project Supervisor Dr. Fahad Mumtaz Malik, MUHAMMAD UMAR FAROOQ SAJJAD ALI MASOOM RAZA MUHAMMAD SAIFULLAH MASUD (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    Pakistan’s critical wireless communication depends heavily on the band 175MHz-225MHz thus making it necessary to effectively monitor and manage this spectrum. It is for this reason that our team is working on the development ...
  • Multi Terminal EV Charging Station with PV Support 
    Project Supervisor Dr Taosif Iqbal, Ehtisham ul Haq Momin Adnan Muzammil Sohail (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    Improvement and clean charging alternatives for electric vehicles (EVs) have continuously learned from their rapid growth recently, which is a big challenge. The idea of this project lies in designing and constructing ...
  • FPGA Implementation of Optimized Deep Learning Algorithm 
    Project Supervisor Dr. Usman Ali, Abdullah Benyamin Muhammad Kashif Nauman Saeed Zoraiz Ahmad (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
  • Microwave Oscillatorand Mixer Design 
    Project Supervisor Dr. Muhammad Anis Chaudhary, Amaan Ali Khan Syed Saqlain Raza Awais Khan (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    Our final year project is the design of a microwave oscillator and mixer. Oscillators and mixers serve as the foundation of many RF front-end systems, and have applications in many areas such as in sensing and ...
  • Solar Wind Hybrid Power System with Battery Storage 
    Project Supervisor DR. TAOSIF IQBAL DR. SALMAN QADIR, Mashhood Ahmad Noman Aftab Zain Aslam (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    The project "Solar Wind Hybrid Power System with Battery Storage" is aimed at developing a robust and sustainable energy solution to meet the critical demand for uninterrupted power supply. In today's dynamic landscape, ...
  • Smart Cane For Visually Impaired 
    Project Supervisor Sobia Hayee, Eman Tanveer Abdullah Malik Mohammad Ammar Muhammad Touseef (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    The goal of the "Smart Cane for Visually Impaired" project was to create cutting-edge assistive technology that would increase the mobility and freedom of people who are blind or visually impaired. The intelligent cane ...
  • Breast Cancer Detection from Mammograms using Deep Learning 
    Project Supervisor Sobia Hayee, NS Amna Muneer NS Fatima Zafar NS Shumaila Naveed NS Waseem Ari (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    Breast Cancer detection with mammography, which is a critical task in medical imaging serves as a primary screening tool. Deep Learning techniques have shown significant improvement in recent years for improving ...
  • AQUABOTIX AI BASED WATER QUALITY ASSESSMENT ROBOT 
    Project Supervisor Asst. Prof Sobia Hayee, Osaid Ahmad Dua Khan Aliya Rubaab (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    The degradation of underwater ecosystems due to pollution and littering presents critical challenges to environmental sustainability. This project introduces AquaBotix, an underwater robot designed for water quality ...
  • GPS-AIDED VISUAL-INERTIAL ODOMETRY FOR SELF-DRIVING CARS 
    Project Supervisor Professor Dr. Fahad Mumtaz Malik, Syed Hamza Ali Usman Ilyas Awan Touha Khalid Farhan Ahmed Abbasi (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    Automated systems are the way the world is going. As for automation, the concept of self driving cars is under significant hype these days as it has significantly reduced the accidents caused by human error. However, ...
  • AI Driven PET-like Synthesis from MRI Data 
    Project Supervisor: Asst Prof Kamran Aziz Bhatti, UMAIR IRFAN SYEDA MAHAM RAZA LARAIB LAIQ NOOR UL AIN ZAHRA (College of Electrical and Mechanical Engineering (CEME), NUST, 2024)
    Our project aims to synthesize Positron Emission Tomography (PET) - Like images from a MRI scan from artificial intelligence (AI) driven models. Dataset used in this regard is of 37 patients each having a T1w, FLAIR and ...
  • Data-driven framework for failure prediction and classification in industrial machines 
    Abid, Aaisha (College of Electrical & Mechanical Engineering (CEME), NUST, 2025-01)
    In this work, an advanced deep learning-based hierarchical diagnosis framework for industrial machinery is presented. The proposed Hierarchical Fault Diagnosis Network (HFDN) model uses a layered architecture to decompose ...
  • Automatic Detection System for the Classification of Tachycardias Using Intracardiac Electrograms 
    Inam ur Rehman, Muhammad (College of Electrical & Mechanical Engineering (CEME), NUST, 2025)
    The Electrophysiology (EP) study is a procedure performed in a catheterization lab to evaluate cardiac electrical activity and identify arrhythmias, aiming to predict potential abnormalities in cardiac rhythm. As an invasive ...
  • A Novel Algorithm for PV Fault Forecasting and Isolating Faulty Locations 
    Khalil, Ihsan Ullah (College of Electrical & Mechanical Engineering (CEME), NUST, 2024)
    Efficient and more reliable operation of solar PV systems contributes effectively to addressing issues such as rising clean energy demand, soaring energy prices, and decarbonization of power generation. With the continuous ...
  • DEVELOPMENT OF SIMPLIFIED ELECTROCHEMICAL MODEL FOR LI ION BATTERY 
    BANO, BEENISH (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-12)
    Advanced battery management systems (BMS) rely on accurate and computationally efficient models of Li-ion cells to ensure optimal operation, as the performance of BMS charging and estimation algorithms is directly influenced ...
  • Performance Evaluation of Wireless Communication System in Critical Propagation Scenarios Using Artificial Intelligence Algorithms 
    TAHIR, BILAL (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-12)
    Modern wireless systems for mobile communication use electromagnetic waves to transmit information over the air, enabling seamless connectivity for a wide range of devices. However, one of the key challenges in wireless ...
  • PLI Removal from ECG Signal using Adaptive Algorithms 
    Javeria Habib (College of Electrical & Mechanical Engineering (CEME), NUST, 2016)
    Electrocardiogram (ECG) is the graphical illustration of heart activity to diagnose various cardiovascular diseases. Presence of Power Line Interference (PLI) in ECG makes it difficult for the examiner to identify proper ...
  • Speed Control of Induction Motor through PI-ANN Controller 
    SIDDIQUE, ZARA (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    An induction motor is also called an asynchronous motor – it is an AC electric motor used extensively in applications. This particular type of motor is utilized in the majority of industrial and commercial electrical ...
  • Integrated Control of Parallel Connected Multiple SEPIC Converters For DC Microgrid Operation 
    ALI, MANZAR (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    DC microgrids are gaining popularity now a days due to their advantages such as improved efficiency, reliability, and renewable energy integration and also due the environmental challenges like carbon and other greenhouse ...
  • Diagnosis of Major Depressive Disorder with a Hybrid Neural Network 
    Haider, Fakhar (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    This thesis employs hybrid neural networks to process electroencephalography (EEG) data to provide an accurate diagnosis of major depressive disorder (MDD). Since EEG Data is of spatiotemporal nature, a hybrid neural ...

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