The Electrical Engineering Department is inviting undergraduate students to apply for research courses for Term 261:
For any questions, please contact the undergraduate research coordinator:
Dr. Abdulaziz Al-Qwbaiban - qwbaiban@kfupm.edu.sa
Project Manager:
Ahmed Abdelmottaleb Abdelfattah Attia Omar
ahmed.omar.1@kfupm.edu.sa
Project Field:
Applied Electromagnetics
Project Title:
Transmissive Polarization Rotator Surfaces for Smart Communication Environment
Project Description:
The project goal is to design a transmissive polarization rotator surface to control the polarization of the EM waves.
Required Skills:
Finish EE340
Project Manager:
Mohammad Nuruzzaman
nzaman@kfupm.edu.sa
Project Field:
Multidimensional Signal Processing
Project Title:
Semi Artificial Intelligent Image Animation
Project Description:
In a fully artificial intelligent system, multidimensional signal systems e.g. images are completely handled by bot or trained computer. Instead of giving full control to bot, human intervention can be injected. Thus, the ethical issue of human replacement can be resolved partially.
Required Skills:
EE207, EE406
Project Manager:
Muhammad Suhail Hussain Shaik
muhammad.shaik@kfupm.edu.sa
Project Field:
Power Systems, power electronics, cybersecurity, communication standards
Project Title:
Cyber Resilient Smart Inverter Control for High Renewable Integrated Grid
Project Description:
This project focuses on improving the security and stability of power grids with high renewable energy penetration by developing cyber-resilient control strategies for smart inverters. As solar, wind, and electric vehicle charging increase on distribution networks, smart inverters play a critical role in voltage regulation, frequency support, and grid reliability. The project will design and evaluate advanced inverter control and adaptive protection methods using real-time simulation and hardware-in-the-loop testing with commercial smart inverters. It will also investigate cyber threats to inverter communication protocols and develop detection and mitigation techniques. Students will gain hands-on experience in power electronics, power system dynamics, cybersecurity, and real-time power system simulation.
Required Skills:
Junior/senior level, programming skills: C / python
Project Manager:
Hussain Abdullah Alzaher
alzaherh@kfupm.edu.sa
Project Field:
Electrical Engineer (electronics circuits)
Project Title:
Characterization and Implementation of the Optimal Op-Amp-Based Quadrature Oscillator
Project Description:
This project aims to investigate, implement, and characterize quadrature oscillator circuits based on operational amplifiers (op-amps). Quadrature oscillators are important building blocks in analog and mixed-signal systems because they generate two sinusoidal output signals with an ideal phase difference of 90°. Such signals are widely used in communication systems, instrumentation, phase-sensitive detection, signal processing, vector generation, and measurement applications.
The main goal of this work is to perform a comprehensive and systematic study of all possible op-amp-based quadrature oscillator topologies available in the literature, and to compare their practical and theoretical performance under a unified framework. Although many oscillator circuits have been reported over the years, they are often presented independently, with limited cross-comparison and without a consistent evaluation methodology. This project addresses that gap by identifying, classifying, analyzing, simulating, and experimentally validating representative op-amp-based quadrature oscillator circuits.
Required Skills:
Good hands-on experience, particularly in circuit implementation and measurement/characterization.
Better than C+ in EE303. GPA is not important; research is different than normal coursework.
Project Manager:
Abdulaziz Al-Qwbaiban
qwbaiban@kfupm.edu.sa
Project Field:
Power Systems
Project Title:
Universal Single-/Three-Phase-Compatible Bidirectional EV Charger with Integrated Low-Voltage DC (LDC) Module
Project Description:
Saudi Arabia’s low-voltage network differs from many regions, with a higher share of commercial loads compared to residential. Homes typically use 220 V single-phase power, while industrial sectors rely on 380 V three-phase systems. This variation makes EV charger design more complex, increasing costs and slowing deployment—especially for large projects like NEOM and the Red Sea under Vision 2030.
This project addresses the issue by developing a universal 6.6 kW / 11 kW bidirectional EV charger that works on both single- and three-phase networks using a single hardware platform. The design includes an adaptable input stage, a high-efficiency isolated DC-DC converter, and a parallel QR flyback module for low-voltage applications like auxiliary batteries and device charging.
Required Skills:
EE 360
Project Manager:
Waleed Mohammed Abdo Hamanah
waleed.hamanah@kfupm.edu.sa
Project Field:
Electrical Power Engineering – Power Systems Reliability and AI-based Condition Monitoring
Project Title:
AI-driven Predictive Health Assessment Framework for Overhead Insulators in Network Power Grid
Project Description:
This project aims to develop a smart system using artificial intelligence (AI) to monitor and predict the condition of overhead power line insulators. In Saudi Arabia, these insulators are exposed to harsh weather conditions such as heat, dust, humidity, and pollution, which can damage them over time and lead to power failures. The project will study real insulators collected from power networks and test their performance in the lab. Data such as leakage current and surface condition will be analyzed using AI models to predict their health and remaining lifetime. The goal is to help power companies detect problems early, reduce unexpected outages, and improve the reliability of the electrical grid.
Required Skills:
Basic knowledge of electrical power systems Familiarity with MATLAB or Python Understanding of high voltage or insulation basics (preferred but not mandatory) Basic knowledge of data analysis or machine learning (intro level is enough) Ability to conduct laboratory experiments and measurements Skills in data collection and report writing Willingness to learn and work in a research team environment
Project Manager:
Marif Siddique
marif.siddique@kfupm.edu.sa
Project Field:
Power Electronics, Electric Vehicle Charger
Project Title:
Design of a Fault-Tolerant Power Electronic System for EV Applications
Project Description:
In the conventional EV battery charging system, two power electronics converters are employed, i.e., AC/DC converter which forms the DC-link voltage, and DC/DC converter for charging the battery. The converter can be of bidirectional nature which can be used for the vehicle to grid (V2G) application. The power semiconductor devices are sensitive to fluctuating operating conditions, which may lead to failures. Most power converter failure occurs due to the failure of either power semiconductors, or capacitors, or gate drivers. Failure of any components can lead to the complete shutdown of the system. The objective of this project is to design a reliable power electronics system for EV applications. The significant objectives of this project are, Fault analysis of the conventional system. Design and simulation of reliable AC/DC Converter and/or DC/DC converter as a part of the proposed system for attaining higher reliability.
Required Skills:
MATLAB, PLECS (optional)
Project Manager:
Marif Siddique
marif.siddique@kfupm.edu.sa
Project Field:
Power Electronics, Artificial Intelligence (AI)
Project Title:
Development of Fault Detection Technique for Power Converter using Artificial Intelligence (AI)
Project Description:
Faults in power converters can lead to performance degradation, reduced efficiency, and even system failure if not detected early. In this project, AI-based techniques will be used to detect and localize faults in power converters, with the goal of improving system reliability, and safety. Real-time operational signals will be analyzed to extract abnormal features and identify fault conditions. AI algorithms will be used for accurate fault classification and precise localization, allowing faster diagnosis and enhanced overall system performance.
Required Skills:
MATLAB, Knowledge of machine learning, neural networks.
Project Manager:
Mohamed Atta Abdulgalil
atta@kfupm.edu.sa
Project Field:
Energy management systems
Project Title:
Resilience- and Uncertainty-Aware Energy Management System for Self-Sustaining Buildings Using On-Site PV and Battery Storage
Project Description:
This project supports the Net Zero mission by advancing the innovation goal of developing self-sustaining building energy generation using on-site renewables, storage, and an advanced energy management system (EMS) by 2030. Buildings in Saudi Arabia represent a major opportunity for decarbonization and peak-demand mitigation, yet the variability of solar generation and the dominance of cooling-driven demand often limit the realized value of PV–BESS systems when operated using rule-based or purely deterministic strategies.
Required Skills:
Basic knowledge of electric circuits. Mathematical and programming skills.
Project Manager:
Abdullah Faisal Al-Battal
albattal@kfupm.edu.sa
Project Field:
Digital Signal and Image Processing (Artificial Intelligence, Computer Vision, Medical Image Analysis, Deep Learning)
Project Title:
Enhancing AI Robustness for Kidney Tumor Segmentation: A Multi-Strategy Approach to Reduce Performance Variability
Project Description:
This project aims to develop and evaluate deep learning methods for automatic kidney tumor segmentation in CT scans. The main goal is to improve the reliability of AI segmentation models, especially on difficult cases. Students will help evaluate AI models on public CT datasets, identify difficult cases where segmentation performance drops, and support experiments designed to make model predictions more accurate and consistent.
Required Skills:
Basic Python programming is required (completion of ICS 104 and ISE 291). Familiarity with machine learning, deep learning, PyTorch, image processing, or medical imaging is preferred but not mandatory (completion of COE 292). Students should be comfortable working with data, reading technical documentation, running experiments, and preparing organized reports and presentations. Good attention to detail, willingness to learn, and ability to work consistently with Python Code and Google Colab or similar tools are important.
Project Manager:
Muneer Ahmed Al Absi
mkulaib@kfupm.edu.sa
Project Field:
Electronics
Project Title:
Time mode Analog to digital converter
Project Description:
One term 062
Required Skills:
Excellent circuits and electronics