Data Science Executive Week 2025

9:30am CDT N201ABC
Capstone OC2-Team2
Title:   Exercise-Based Prediction of Hyper- and Hypo-glycemia in Youth with Type 1 Diabetes
Project Description: Managing blood glucose levels in youth with Type 1 Diabetes (T1D) is challenging due to the complex relationships between glucose levels, exercise, insulin, heart rate, physiological attributes, and other factors. Many youth with T1D fear hypoglycemia after exercise and may overconsume calories beforehand, increasing the risk of hyperglycemia. These glucose fluctuations often discourage them from engaging in physical activity. Our project aims to develop a predictive model to classify the occurrence of hyperglycemia and hypoglycemia events within two hours after exercise. Our findings are primarily targeted toward clinicians and researchers to enhance understanding of glucose regulation in relation to exercise, with the potential to later assist youth and their parents in making informed decisions about safe physical activity.
Master Students: Chun-Chih Chin, Xiling Guo, Jeong Wook Lee, Aakash Unnam
 
10:00am CDT N201ABC
Capstone OL-Team3
Project Title: Born to Be Data-Driven: Pushing the boundaries on our understanding of preterm birth
Project Description: Childbirth and infant health are critical areas of study that impact both individual families and our society. This project focuses on understanding factors associated with preterm birth using 2022 U.S. birth data. It aims to improve maternal and infant health outcomes by reaching healthcare professionals and the general public.
Master Students: April Oga, Katarina Salcedo, Ramyaa Manoharan, Fatema Cheema, Germaine Knox