Electrical and Computer Engineering
Faculty Mentor: Dr. Eddie Jacobs
Faculty Mentor's Department: Electrical and Computer Engineering
Contact Information: email@example.com
Project Description: This project involves the creation of detailed maps of the interiors of buildings
with items of interest to first responders clearly labeled. We use 3D LIDAR sensors
and 3D cameras to generate point cloud representations of the interiors of buildings.
We then use machine learning and artificial intelligence to refine and label these
Requirements for Student Applicants: Majoring in Electrical Engineering, Computer Engineering, or Computer Science.
Application or Interview Process: Email with declaration of interest and a resume. This will be followed with an in person interview.
Hours per Week the Student Will Work: 10+
Starting Date: Immediately
Method of Compensation: Volunteer
Faculty Mentor: Dr. Chrysanthe Preza
Department: Electrical & Computer Engineering
Contact Information: firstname.lastname@example.org
Project Description: Much research has been conducted in computational optical sectioning microscopy (COSM) - a technique used widely in microscopy for the non-invasive visualization of three-dimensional (3D) samples labeled with fluorescence dyes- over the years resulting in both open source (http://cirl.memphis.edu/cosmos/) and commercially available software. The goal of this project in Computational Imaging Research Laboratory (CIRL) is to develop new corrective methodologies for COSM that are suitable for imaging thick samples. Refractive index mismatch and heterogeneity within thick samples produce image distortions that worsen with imaging depth in conventional microscopes. These distortions not only reduce image resolution but also they result in image processing artifacts when the data are processed with algorithms (software) that are based on a thin-sample imaging model. The research is based on a novel and innovative approach that integrates computational development with a new imaging system design that includes structured illumination. Specific research includes 1) developing mathematical models that can accurately predict data acquired with the novel imaging system; 2) developing and testing model-based data processing algorithms to estimate accurate fluorescence concentration in 3D images; and 3) developing a software package for the user community. Performance and utility of the new methods is being tested on data from test objects and biological samples. Students selected for this project will have the opportunity to participate in different aspects of this interdisciplinary research based on student skills and interests.
Requirements for Student Applicants: Majoring in Electrical Engineering, Computer Engineering, Computer Science, Physics, and Biological Sciences; GPA 3.0 or higher
Application or Interview Process: Unofficial transcripts
Hours per week the student will work: 10-20 hours/week
Start Date: Immediately
Methods of Compensation: Volunteer