2023 Projects
A team of students will analyze, map, and visualize student enrollment and demographic data in Durham County. The team will collaborate closely with analytics professionals at the Durham Public Schools (DPS) operations department and will provide analysis to help DPS plan and manage student enrollment and improve fairness in its...
A team of students led by Physics professor Dan Scolnic will collaborate with Duke Dining leadership to provide an in-depth, quantitative accounting of the carbon footprint of the Duke Dining program. Students will use the latest research quantifying CO2 equivalent greenhouse gas emissions for various food types, meals, and sources...
A team of students led by researchers in the O-Lab for auditory neuroscience will determine whether the imagination of speech and nonspeech sounds can be distinguished using on a non-invasive measurement of activation in the brain, electroencephalography (EEG). Students will collect and analyze EEG data from human participants in response...
A team of students led by professors Maurizio Forte, Classical Studies and AAHVS and Leonard White, Neurology, will study the embodied aesthetic experience engendered by real and virtual interactions with archeological ruins (“ruinscapes”) and virtual representations of places, spaces, and cultural artifacts associated with an ancient city. The focus will...
A team of students led by Prof. Zuchuan Li and co-led by Prof. Nicolas Cassar will develop means to estimate the amount of CO2 transferred from the ocean surface to the deep ocean through machine learning techniques applied to satellite data and automatic observations. Students will identify variables that can...
A team of students will collaborate with Biostatistics & Bioinformatics Professor Ethan Fang, and Fuqua Professor Yehua Wei to develop new algorithms for hospital scheduling. Optimal hospital scheduling will fully utilize the resource of the hospital and reduce the wait time of the patients. The new algorithm will lead to...
A team of students led by Biostatistics & Bioinformatics Professor Ethan Fang and Surgery Professor Annette Jackson will explore automatic transplant matching. Students will build an automatic system to mine the HLA dataset to predict whether a donor and a receiver is a potential match. This work will help the...
A team of students led by researchers in the Hydroclimatological Lab will create a workflow/pipeline for comprehensively estimating the carbon emissions from the Southeastern (SE) United States (US) wetlands using machine learning techniques applied to multi-source data, including field measurements, remote sensing products, and biophysical model outputs. Students will first...
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