2025 Projects
Students will create accessible, actionable data on climate risks and climate resilience efforts in the Milwaukee River area. By harnessing existing data sources as inputs for hazard modeling, focused on flooding, students will use techniques to account for uncertainties in inputs, providing more accurate and adaptable risk assessments for communities....
Despite the vast amount of admissions data we collect, there is still limited understanding of what factors are most predictive of admitted students’ decision to attend Duke. Traditional yield models have focused on a small set of variables that have limited power in predicting students’ decisions, and there may be...
This team created “The Survey Navigator,” an interactive platform that helps users discover, compare, and visualize public opinion data. Led by professors Sunshine Hillygus and Alexander Volfovsky, and supported by Duke’s Polarization Lab, we will harness the power of statistics, machine learning, and AI to transform raw survey questions into...
Students will curate administrative data to conduct Sequence Analysis (SA), a technique used to analyze patterns in sets of categorical sequences over time. Traditional education reports often rely on cross-sectional data (e.g., proportion of students under economic disadvantage), and in tend to overlook the chronic exposure to disadvantages that longitudinal...
This is an innovative project that explores the intersection of artificial intelligence and mathematics. This initiative aims to leverage AI’s capabilities in pattern recognition and exhaustive search to tackle complex problems in discrete mathematics, such as finding counterexamples to open conjectures. By framing these mathematical challenges as computational problems, students...
This data expedition focused on biological senses, in particular, musicality. The students read and summarized four scientific articles in discussion groups to build their background knowledge when it comes to how humans and animals use pitch and rhythm in music, language, and songs. We then had each student use headphones...
The course was designed as a Data Expedition to familiarize senior-level undergraduates with data collection and analysis. We ran the course during the lab section of BIOL 546L on the topic of hair as a mammalian adaptation. Students created testable hypotheses, compared fur/hair samples between species, and graphed their group’s...
Graduate Students: Aeran Coughlin and Richard J Wong Sponsoring Faculty: Danae Diaz Undergraduate Course: Biology 290S – 3: “Biology By Design” This data expedition focused on plant communities, ecological data exploration, quantifying diversity, linear and generalized linear models, and ordination. Prior to the data expedition, students collected field data in...
Graduate Students: Alyvia Martinez and Danae Diaz (adapted from Granger and De La Mater 2022) Sponsoring Faculty: Dr. Stephen Nowicki Undergraduate Course: Biology 268-Mechanisms of Animal Behavior Overview: Our Data Expedition focused on introducing students to the application of circular data in regard to animal navigation. Students worked in groups...
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