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Big Ideas Lab, Pratt School of Engineering at Duke University

Using wearable technology to detect early symptoms of COVID-19

Status: Ongoing
Start and End Date: (Summer 2020 – Spring 2021, Summer 2022 -)

I was actively involved in the CovIdentify Project at the Big Ideas Lab during the initial stages of the COVID-19 pandemic. The primary objective of the CovIdentify Project is to construct machine learning models using data collected from wearable devices, such as heart rate, step count, and sleep activity, in order to predict early symptoms of COVID-19. This endeavor involves enlisting participants and capturing data from their wearable devices to gather essential biomarkers. Furthermore, the study is augmented by daily symptom monitoring surveys, which participants can access through a smartphone application or via email.

My contributions to the project encompassed a range of tasks, including the development of data pipelines for processing wearable device data, analyzing and visualizing data from the symptom monitoring surveys, and actively engaging in participant recruitment efforts. For more detailed information, please visit: CovIdentify Project

More recently, I’ve focused on respiratory illness detection in a controlled clinical setting by partnering with the NIAID Collaborative Influenza Vaccine Innovation Centers (CIVICs) Flu Challenge Project. We aim to test early detection algorithms using wearable devices on flu-inoculated participants.

GC Focus Connection:
This interdisciplinary project focuses on precision medicine and science communication, both of which are crucial to my GC goals. With large omics data in tissue engineering, the data analysis and machine learning skills I learned in this project will be crucial for creating personalized medicine in tissue engineering. In addition, the science communication skills I learned is important for conversing ethical issue surrounding tissue engineering as well. This project tackles the scientific research and interdisciplinary component of my GC goals.

Segura Lab, Pratt School of Engineering at Duke University

Using MAP hydrogel to increase M2 macrophage growth for wound healing applications

Status: Completed
Start and End Date: (Spring 2021 – Fall 2021)
In Segura Lab, I worked on applications with Microporous Annealed Particles (MAP) hydrogels. MAP hydrogel is a new class of injectable biomaterial that provides an interconnected microporous network, increasing tissue reformation and material degradation. Specifically, I worked with a graduate student to investigate how the microporosity of MAP hydrogels increase M2 Macrophages proliferation. Increased proliferation of M2 macrophages ultimately leads to faster wound healing and tissue regeneration. My task was to make the MAP hydrogels, and image and analyze cells grown under different mesh sizes of MAP hydrogels.

GC Focus Connection:
Investigating wound healing with MAP hydrogels is closely related to my interest in using synthetic biology for tissue regeneration. I seek to build on this study and investigate how MAP hydrogels may affect stem cell growth and differentiation in tissue regeneration, and work towards my goal to create personalized medicine. This research tackles the scientific research component of my GC goals.