Global Local Engagement
About GLE
Global-Local Engagement (GLE) is a meaningful experience that allows students to apply their Pathway’s animating question to a real-world context, either within their local community or in a global setting. The goal of a GLE is to deepen students’ understanding of their thematic focus through hands-on learning, community involvement, or practical application of knowledge. This can take many forms, such as internships, research projects, study away programs, or community-based initiatives. By connecting classroom learning to lived experiences, GLE helps students explore how their academic interests intersect with societal needs, ethical concerns, and professional fields of practice.
Synthetic Data Creation in Biology Lab
Organization: Professor Douglass Metagenomics Lab
Position/Role: Student Researcher
Time Frame: Summer of 2025
Description: For my Global-Local Engagement, I was a student researcher in Professor Douglass’ metagenomics lab. In this role, I wrote software that generates synthetic sequence reads that align closely with PacBio’s High-Fidelity reads, which can be used to test and improve computational tools before applying them to real biological datasets. This experience aligns closely with my animating question by allowing me to explore how synthetic data can be used to enhance scientific research, particularly when real data is incomplete, biased, or difficult to obtain. This experience allowed me to engage directly with the technical challenges of designing realistic synthetic data. Additionally, this project gave a unique perspective on the use of data generation to perfect scientific tools. Overall, this experience grew my understanding of the process behind synthetic data generation in terms of technicality, use, and functionality. This software, while being used by Professor Douglass’ lab, is currently not public. As a next step, I am working on publishing my tool so that all researchers working with sequencing can benefit from the simulated sequence reads.