A team of students led by the Duke World Food Policy Center’s Ag economist Norbert Wilson and electrical and computer engineering professor Leslie Collins and research professor Boyla Mainsah will analyze agricultural research funding to understand whether USDA’s National Institute of Food and Agriculture (NIFA) has prioritized Ag production and...
A team of students will collaborate with the UNC Injury Prevention Research Center and North Carolina Injury and Violence Prevention Branch to update the North Carolina Alcohol Data Dashboard. Students will analyze data, design a dashboard wireframe, and build an updated data dashboard that provides a holistic narrative of the...
Alzheimer’s alters brain connectivity beyond local regions. Understanding necessitates a shift from dyadic to higher-order relations naturally expressed in the language of algebraic topology. Led by professors of Computer Science and Neurology, Dr. Tananun Songdechakraiwut, Dr. Michael Lutz, and Dr. Jian Pei, an interdisciplinary team of students will investigate intricate...
A team of students, guided by computer vision lab researchers and the coaching staff of Duke Women’s Basketball, is set to create a suite of tools designed to automatically analyze gameplay from video clips using computer vision techniques. They will construct a computer vision application capable of pinpointing players’ positions...
A team of students led by researchers in Energy Materials and Machine Learning groups, supervised by Prof. Olivier Delaire and Prof. David Carlson, will develop means to evaluate and quantity motions of atoms in novel materials for energy conversion and energy storage. This project will advance our understanding of two...
A team of students will collaborate with the Durham Public Schools (DPS) planning department to analyze, map, and visualize student enrollment and demographic data in Durham County. This data will help DPS plan and manage student enrollment and improve fairness in its student assignment policies. The main project will be...
A team of students led by an interdisciplinary group including statistician Fan Li, neurologist Brian Mac Grory, and physician/population health scientist Jay Lusk will integrate information from diverse real-world datasets to better understand risk factors for cardiovascular diseases such as heart attack and stroke. The team will use techniques ranging...
In collaboration with Duke’s River Center, a team of students will use remote sensing, in-situ water quality data, and machine learning algorithms to detect saltwater intrusion in coastal rivers. As sea levels rise, coastal waterways will become increasingly saline, threatening freshwater biodiversity and ecosystem services. Students will develop a harmonized...
A team of students led by Duke Forest staff as well as a faculty and postdoc from Duke’s Nicholas School of the Environment will explore, organize, and create visualizations for observation data of reptiles and amphibians—collectively known as “herpetofauna”—in the Duke Forest. This data is directly collected by Duke Forest’s...
A team of students led by researchers in the Energy Access Project and the Energy Data Analytics Lab will apply machine learning techniques to high resolution aerial imagery data to identify the location of solar panels throughout Cape Town, South Africa. Currently, solar panels are being used by wealthier households...
Students will develop and use a database that links physical, chemical, and social environmental data with incidence of specific immune-related diseases within neighborhoods in North Carolina. This database will consist of both publicly-available environmental, social, and climate data as well as data specific to/generated by Duke researchers; health information will...
Is it ethically permissible to sell, buy, and use luxury goods? What labor practices do we tolerate to make these goods available? This project traces the early history of these questions as European powers started to exploit the natural resources and peoples of the New World. We want to trace...
A team of researchers associated with the Applied Machine Learning Laboratory will lead a team of students in developing novel machine learning techniques that will be used for improving brain computer interfaces (BCIs) using electroencephalography (EEG) data. Students will learn how to pre-process EEG data, extract EEG features, and train...
The US has one of the largest incarcerated populations per capita; prisons are dangerous environments with high in-prison and post-release mortality. Our 3rd City Mortality project tracks near-real-time data about individual deaths, including data completeness and release speed, across US state, federal, and Washington DC prison systems. Students will use...
A team of students led by researchers in the BIG IDEAs Lab will optimize and further develop an existing cloud-based infection detection platform that populates and translates wearable data from a variety of sources. The project will involve working with existing wearable data pipelines (e.g., APIs) to collect, process, and...
A group of students led by professors of climate sciences and stochastic analysis will use climate models to improve the projected rainfall over the southeastern United States. Students will learn about the climate processes that influence precipitation, flooding, and droughts, as well as how to improve model capability to predict...
A team of students will collaborate with the Duke Health Digital Strategy Office, led by Associate Medical Director Joanna S. Cavalier, MD, to analyze data on patient-reported outcomes and patient questionnaires to improve patient experience and care. Our electronic health record, Epic, has a released a new data set that...
A team of students led by Biomedical Engineering Professor Megan Madonna and the Center for Global Women’s Health Technologies will develop methods to explore how middle and high school students become excited about engineering and STEM. Our team will evaluate and quantify the initiation and progression of engineering and STEM-identity...
Students will analyze data on climate risk, most likely including flood risk, perhaps a combination of public data, private data, and insurance sector data for pilot communities in North Carolina. They will integrate this data with other local data sets such as critical community infrastructure (schools, hospitals) and provide visualization...
In partnership with the Southeast Regional Coalition for University-Assisted Community Schools and the North Carolina Community Schools Coalition, a team of students will map the Rosenwald Schools across the Black Belt region of North Carolina. Students will mine for data that highlights historic assets of Black community while drawing correlations...
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