Research

The Electrical Engineering faculty members have active research in the following areas: 

Applied Electromagnetics

• Ultra Wideband (UWB) Microwave Tomography: Microwave tomography is noninvasive method to image and obtain characterization of objects. Our focus is on both hardware design including UWB antenna design, and software development for inverse imaging. 

• Spacesuit Antennas: Wideband communication is desired for Extra Vehicular Activity (EVA). Antenna design is a crucial step towards this goal. Our focus is on designing low power high gain antennas and adaptive arrays. 

• Wireless Channel Characterization: The demand for anytime, anywhere connectivity is increasing. Design of reliable and efficient wireless networks requires better knowledge of wireless channels. We focus on characterization of wireless channel and design of adaptive arrays for different environments. 

Biomedical Engineering

• Brain Signal (EEG) Characterization: EEG signals are characterized with a research focus on human epileptic seizure application. The goal of this research project is to introduce an innovative hybrid method in characterizing brain signals for predicting and detecting epileptic seizure.

• Brain Computer Interface: A brain-computer interface (BCI) technology can convey messages and commands directly from the human brain to a computer to be used as a control signal. The team is looking into the application of BCI in designing virtual keyboard, smart home system, lie detector, and computer games. 

• Human Performance Evaluation: This is another focus of the biomedical engineering team in which the performance of subject activity are measured based on physiological signals such and brain and heart signals. The method is applied for NDX-1 and NDX-2 space suits evaluations. 

Embedded Systems Design and Configurable Computing

As the number of computing systems worldwide exponentially increases the pressure to reduce power consumption and losses increases as well. Because Processor-based systems cannot meet this challenge, digital programmable devices-based systems, such as FPGAs, will be crucial in the design of the next generation of green computing systems. Projects under this area focus on designing FPGA-based systems and comparing their performances to those Processor-based systems.

Power and Energy Systems

Power and energy related research projects are focused on several topics including smart grid, demand response, electric drives, power electronics, conventional electric power systems as well as alternative and renewable energy systems, fuel cells and water electrolyzers and their modeling and control issues, load control and energy management, power systems state estimation, neuro-fuzzy intelligent decision systems, and power systems reliability. A brief description of current projects follows. 

• Demand response and integration issues of diverse and distributed energy resources into smart grids are focal points of current research work at UND. 

• Using a combination of power electronic controllers and Texas Instruments' digital signal processing (DSP) boards, an efficient vector control technique for induction machines is designed and developed. Through the support of a National Science Foundation (NSF) grant, work has been done to extend this research project to sensorless vector control of electric drives. 

• Currently work is underway to model and investigate the frequency control and voltage stability issues of grid connected wind turbine generators. 

• With support from the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) in Golden, Colorado, and in collaboration with colleagues from Chemical Engineering Department at UND, two (2) advanced experimental research facilities to investigate the modeling, performance, and control issues of integrated wind turbines-to-electrolyzer-to-hydrogen production-to-fuel cell energy systems have been established. Using electrochemical impedance spectroscopy (EIS) technique, a part of these facilities is used to experimentally model and verify PEM fuel cells and electrolyzers. 

• The primary focus of other recent projects is to investigate and develop advanced artificial intelligent models to predict the level of mercury emissions into the environment from coal-fired electric power plants located throughout the nation.

For more details on please refer to:

Learn more about Power Electronics

Learn more about the Hydrogen to Power Laboratory 

Signal/Image Processing

Several projects related to signal/image processing are performed in EE department. These projects include:

• Mosaicking/Super-Resolution

This project aims to develop super-resolution mosaic s from low-resolution UAS surveillance video frames, so that effective image analysis can be conducted. Mosaicking refers to the stitching of one or more correlated images, forming a much larger image of a scene. Super-resolution mosaicking refers to methods for enhancing the resolution of the mosaic, which can be affected by different sources of noise, as well as other effects such as camera translation and rotation.

• Early Detection/Prediction of Foot Ulcers

Foot Ulcers is a disease that affects millions of Americans each year. This project aims to develop tools and techniques to detect foot ulcers before they can develop. It is a collaborative project between the Electrical Engineering department, Mechanical Engineering department, and the College of Nursing.

• TeraHertz Imaging as a Non-Invasive Technique for Cancerous Cells Detection    

The long term goal of this research project is to develop a terahertz imaging system that can detect cancer at the cellular level.  The project is a collaborative effort between the Electrical Engineering department and the School of Medicine and Health Sciences in the area of cancer detection with terahertz imaging technology.

• Gel Electrophoresis and Microarray Image Analysis

 Gel electrophoresis and microarray data analyses are two widely used techniques for genetic studies, require the bench scientist to perform many tedious and time consuming manual steps. The objective of this project is to develop advanced automatic techniques and systems to allow researchers to speed up their analyses and to obtain more repeatable and accurate results.

Space Systems Development

Space systems development related research projects focus on several topics, including:

• Unmanned Aerial Systems (UAS)

Projects in this area focus on solving several problems including payloads design, sense and avoid, Lost Link, jamming, communications protocols, high frequency communications systems for unmanned aerial systems, mosaicking and super resolution of UAV video frames. These are collaborative projects between the UND Electrical Engineering and Mechanical Engineering departments.   

• Manned/Unmanned Ground Vehicles (Robotics)

The project gives the students the opportunity to construct autonomous robots for space applications. One example of these robots is the Lunabot, a robot designed to autonomously collect regolith—a sand–like material important in building a moon base. This robot is used by an EE and ME team to compete with teams from other universities during the NASA Lunabotics competition held in the NASA Kennedy Space, Florida.

• High Altitude Balloons

The High Altitude Student Platform (HASP) is a project that provides student groups with access to the near-space environment using zero-pressure high-altitude balloons.  This project which started in 2008 is a collaborative project between departments from two universities, the UND Electrical Engineering Department, The UND Space Studies Department, and the University of Florida.

Wireless Sensor networks

• Decision support and self-healing mechanisms for Smart Grid. Development of analytical and computational tools for optimization of large-scale integrated systems such as power, control, and communication systems.

• Time synchronization in sensor network applications (distributed system) that require very precise mapping of gathered sensor data with the time of the events, for example, in tracking and vehicular surveillance.

• Computational complexity and circuit design analysis.