2021 Projects
Heidi Smith (CS, English) and Biniam Garomsa (DataScience, Math) spent ten weeks building tools to assist the David M. Rubenstein Rare Book and Manuscript Library’s mission of finding and describing historically marginalized voices within their collections. The team performed extensive data wrangling, including modern optical character recognition techniques, with the...
Is there a right type and amount of consumption? The idea of ethical consumption has gained prominence in recent discourse, both in terms of what we purchase (from fair trade coffee to carbon off-sets) and how much we consume (from rechargeable batteries to energy efficient homes). Concern with the morality...
Tejvasi Patil (MEM), Sophia Stameson (CS), and Larry Zheng (Bio) spent ten weeks working with drone footage from different rainforest sources. The team designed a pipeline that performed image classification on the drone footage, and curated a training dataset using SQL. View the team’s project poster here Watch the...
Project Summary Evan Dragich (Stats/Bio) and Katie Tan (Econ) spent ten weeks working with two sets of survey data provided by alumni of the Duke Graduate School. After cleaning data, the team used R Shiny to build an interactive dashboard that can assist leadership aiming to improve the direction and...
Annie Xu (Rice, CEE), Liuren Yin (ECE), and Zoe Zhu (Data Science) spent ten weeks analysing usage data for MorphoSource, a publicly available 3D data repository maintained by Duke University. Working with Python and Tableau, the team developed an interactive dashboard that allows MorphoSource staff to explore usage patterns for...
Molly Borowiak (CS) and Joshua Tennyson (CS/BME) spent ten weeks building tools to assist in the analysis of data arising from microbial growth experiments. The team produced a comprehensive Python package that enables the exploration of a variety of modeling techniques with the data. View the team’s project poster...
Jayesh Gupta (ECE/CS), Trevon Helm (ECE), and Yvonne Kuo (CS/PoliSci) spent ten weeks developing tools to extract features from network data in collaboration with information security professionals with Duke’s OIT. The team performed exploratory data analysis to extract features and used machine-learning techniques to detect zero-day attacks. This project was...
Stats majors Alexandra Lawrence and Morgan Pruchniewski spent ten weeks exploring a dataset comprising 619 variables, including chemical and biological measurements, sourced from the Pivers Island Coastal Observatory (PICO). Using modern time-series analysis techniques, the team delivered key insights to PICO scientific staff, as well as advice for future data...
Sean Fiscus (Math/Econ/EnvEng), Alyssa Shi (Stats), Yamil Lopez-Ruiz (BME/CS), Emmanuel Mokel (Stats/Math) spent ten weeks working with data from CovIdentify, a study that focuses on using wearables to predict and diagnose COVID-19 and the Flu. The team improved the memory efficiency of analytic pipelines, and added capacity to ingest different...
Simi Bleznak (Math/AI), Max Brown (Math/Econ), and Julia Choi (Bio) spent ten weeks Exploring how visual, cognitive, and physical abilities relate to physical performance can provide insight into the development of athletes. Using two rich datasets provided by USA Baseball, the team used linear regression, logistic regression models, and longitudinal...
Martin Guo (MIDS), Dani Trejo (CS), James Wang (CS/Math), and Grayson York (Math/CS) spent ten weeks building tools to understand voting patterns and gerrymandering of districts in North Carolina. They used dimension reduction techniques to cluster different elections into common groups, and they tested various methods for generating synthetic elections...
Caroline Tang (Math/Stats) joined CS majors Frankie Willard and Alex Kumar in a ten-week exploration of AI methods to improve the mapping of energy infrastructure within satellite imagery. The team used cutting-edge methods to create synthetic imagery that, when blended with real imagery, improved the performance of deep learning methods...
Louis Hu (CS/Math), Fayfay Ning (Math/CS), and Kieran Lele (CS/Sociology) spent ten weeks exploring methods for exploring the similarities between networks of massive size, such as those arising from social media or from protein-protein alignment. The team used a variety of mathematical and software techniques and delivered a comprehensive analysis...
Keith Cressman (CS/ECE), Isa Lu (Econ), and Ivan-Aleksandr Mavrov (Econ/Math) spent ten weeks exploring how NLP tools could be put to use to improve document analysis workflow at DUMAC Inc., which is responsible for managing the assets of Duke University. View the team’s project poster here Watch the team’s...
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