Openings

 

The Gleason Lab is currently is looking for dedicated, curious, and creative Georgia Tech undergraduates to join one of three project teams. Each team aims to combat pregnancy complications faced by Ethiopian women through development of innovative, low-cost, and high impact engineering solutions. Fall 2020 and Spring 2021 positions are available. Please read below for details on the positions, and apply here! Please direct questions to Elianna Paljug at elianna@gatech.edu and see https://sites.gatech.edu/gleason-lab/ for more information. Applications are due Monday, July 27th. Entirely remote opportunities are available for all projects. Decisions will be made before Phase 2 registration.

Apply to join the Gleason Lab!

 

Photoplethysmography Sensor Device Development – Early Diagnosis of Preeclampsia

We are currently searching for BME students, preferably with a CS/ECE minor, or ECE or CS students. The expected commitment would be for Fall 2020 and Spring 2021 and involves working in both group and individual settings. The focus of the project is the development of a low-cost photoplethysmography (PPG) biomedical device for the identification of hemodynamic markers that may predict preeclampsia risk of pregnant mothers in the developing countries, for a clinical study in Addis Ababa, Ethiopia. For the Fall 2020 semester, research topics will include (but are not limited to) signal processing, data analysis, user interface development, sensor validation and verification, and preparing the device for clinical trials.

Strongly preferred experience: BMED 2250, CS 1371

Preferred Experience: ECE 3710, BMED 2400, Arduino/microcontrollers, Matlab app development, rapid prototyping, signal processing, data analysis

 

Paper Microfluidic Device Development – Early Diagnosis of Preeclampsia 

We are looking for students to join our team beginning in the Fall of 2020. Our project is focused on designing a simple, low-cost method to detect preeclampsia early in pregnancy, for a clinical study in Addis Ababa, Ethiopia. Currently, the project has two main focuses: a paper-based microfluidic colorimetric device, and a color detection app. The goal is that, when exposed to certain biomarkers, a reaction will occur in the microfluidic channels that causes a visible color change, which can then be photographed with a phone app that will quantify the amount of the biomarker present based on the degree of change. This semester we will focus on the design of the paper device, and the testing of reactions with various biomarkers. The project incorporates colorimetry, microfluidics, biochemistry, nanoparticles, and point-of-care device design. Basic knowledge of antigen/antibody interactions, lateral flow or paper microfluidics, and antibody conjugation are recommended. Our current students are biomedical engineering majors, but we are open to people from multiple areas, including computer science, biology/biochemistry, chemical engineering, and pre-med. Students with previous experience with paper microfluidics or later flow assays are especially strong candidates. If you are interested in learning more, we would love to hear from you.

 

Cephalopelvic Disproportion Assessment Algorithm Development – Prediction of Obstructed Labor 

This project is focused on the development, testing, and app integration of an algorithm that calculates a risk score for pregnant women’s chance of having obstructed labor due to cephalopelvic disproportion, a common pregnancy compilation that contributes largely to maternal and infant mortality in countries without readily available access to cesarean sections. The risk score is calculated using a novel algorithm that obtains anthropometric measurements from 3D scans of pregnant women which are taken with Structure Sensor 3D cameras, or Kinect 3D cameras.  This project involves supporting an ongoing clinical study in Addis Ababa, Ethiopia through data analysis and algorithm improvement in MATLAB, and could also involve app development of tools for the study and/or tools for the final product to be in clinical use. Preferred students are those experienced with MATLAB or with app development, and/or students who are available to work on the project for multiple semesters.