John Benhart (CompSci, Math) and Esko Brummel (Masters in Bioethics and Science Policy) spent ten weeks analyzing current and potential scholarly collaborations within the community of Duke faculty. They worked closely with the leadership of the Scholars@Duke database. Project Results: The team built an interactive similarity network of Duke scholars, with weighted edges derived from textual...
This project is also part of Duke’s first Climate+ cohort. A team of students led by researchers at Duke and abroad will develop and evaluate machine learning solutions to model behavioral patterns of electric use, emphasizing data privacy. Data collected in different parts of the world will be analyzed to...
A team of students led by Professor Anru Zhang (Duke Biostatistics & Bioinformatics, Computer Science, Mathematics, and Statistical Science) will develop methods to investigate the courses of complex diseases through electronic health records. The team will apply tensor methods to identify key features to register the patient’s timeline. This work...
A team of students led by Prof. Zuchuan Li and co-led by Prof. Nicolas Cassar developed 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. The team identified variables that can be...
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...
Nathaniel Choe (ECE) and Mashal Ali (Neuroscience) spent ten weeks developing machine-learning tools to analyze urodynamic detrusor pressure data of pediatric spina bifida patients from the Duke University Hospital. The team built a pipeline that went from raw time series data to signal analysis to dimension reduction to classification, and has the potential...
A team of students led by researchers in the Social Science Research Institute and Departments of Mathematics and Statistics curated a unique video data set for studying how different aspects of social interactions relate to social and psychiatric variables, like trust, empathy, and scores on clinical social competence and autism...
A team of students led by researchers in the Computer Science Department and the coaching staff of the Duke Women’s Soccer (DWS) team developed analytical tools to provide quantitative evaluations of individual players and whole teams. By applying machine learning techniques and other data science methods to deep event-level and...
Alexandra Putka (Biology/Neuroscience), John Madden (Economics), and Lucy St. Charles (Global Health/Spanish) spent ten weeks understanding the coverage and timeliness of maternal and pediatric vaccines in Durham. They used data from DEDUCE, the American Community Survey, and the CDC. This project will continue into the academic year via Bass Connections. Click here to read the Executive Summary...
Furthering the work of a 2016 Data+ team in predictive modeling of pancreatic cancer from electronic medical record (EMR) data, students Siwei Zhang (Masters Biostatistics) and Jake Ukleja (Computer Science) spent ten weeks building a model to predict pancreatic cancer from Electronic Medical Records (EMR) data. They worked with nine years worth of EMR data, including ICD9 diagnostic codes, that...
A student team led by Henry Pfister’s research group will develop and evaluate an AI-powered “visual assistant” that pairs smart glasses with modern visual language models to assist people with visual impairment. We’ll start by benchmarking models on the VisAssistDaily dataset and then prototype a real-time system using open-source multimodal...
A team of students collaborated with researchers from the National Diaper Bank Network / the Diaper Bank of North Carolina (Kelley Massengale) and Duke Department of Pediatrics (Rushina Cholera) to assess characteristics of diaper bank recipient families. Utilizing the largest dataset of information provided by families accessing diaper banks, students...
Patience Jones (NCCU, Psychology and Elementary Education) joined Duke students Allyson Ashekun (PubPol), Drew Greene (PubPol), and Rhea Tejwani (CS/Econ) in a ten-week curation of data meant to assist decision-makers within Durham Public Schools. Using data from the Durham Compass and the NC School Report Card among many other sources,...
Using data from the Durham Compass and the NC School Report Card among many other sources, this team will continue the development of an interactive R Shiny dashboard that permits exploration of school statistical data. The team aims to explore school zones through an asset-based lens in an effort to support ethical...
Over ten weeks, Computer Science majors Daniel Bass-Blue and Susie Choi joined forces with Biomedical Engineering major Ellie Wood to prototype interactive interfaces from Type II diabetics’ mobile health data. Their specific goals were to encourage patient self-management and to effectively inform clinicians about patient behavior between visits. Project Results: The team worked with patient data from...
This project, conducted during a two-week workshop, combined data extraction from a database of early modern print materials (Early English Books Online; EEBO) with the translation of archival evidence through visualizations of networks relating to prominent figures in the trade.
Robbie Ha (Computer Science, Statistics), Peilin Lai (Computer Science, Mathematics), and Alejandro Ortega (Mathematics) spent ten weeks analyzing the content and dissemination of images of the Syrian refugee crisis, as part of a general data-driven investigation of Western photojournalism and how it has contributed to our understanding of this crisis. Project Results: The team gathered...
Our project will see a team of students digitize, curate, and host a wide-ranging historical dataset pertaining to the Egyptian cotton industry over the course of the interwar period and Great Depression. Students will apply Optical Character Recognition (OCR) tools to English and Arabic statistical sources ranging from government journals...
Jennie Wang (Economics/Computer Science) and Blen Biru (Biology/French) spent ten weeks building visualizations of various aspects of the lives of orphaned and separated children at six separate sites in Africa and Asia. The team created R Shiny interactive visualizations of data provided by the Positive Outcomes for Orphans study (POFO). Executive Summary (PDF) Project...
Yoav Kargon (Mechanical Engineering) and Tommy Lin (Chemistry, Computer Science) spent ten weeks working with data from the Water Quality Portal (WQP), a large national dataset of water quality measurements aggregated by the USGS and EPA. The team went all the way from raw data to the production of Pondr, an interactive and...
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