Brianna Cellini (Global Health, Neuroscience), Kexin (William) Feng (Public Policy, Philosophy), John Liakos (Neuroscience), and Maya Pandey (Political Science, Public Policy) received updated data from the Durham county sheriff’s office and Duke health, adding data from 2019-2020. They spent the summer cleaning that data, comparing past demographics and descriptive statistics...
Over ten weeks, Computer Science Majors Amber Strange and Jackson Dellinger joined forces with Psychology major Rachel Buchanan to perform a data-driven analysis of mental health intervention practices by Durham Police Department. They worked closely with leadership from the Durham Crisis Intervention Team (CIT) Collaborative, made up of officers who have completed 40 hours of specialized training in mental illness...
Tatanya Bidopia (Psychology, Global Health), Matthew Rose (Computer Science), Joyce Yoo (Public Policy/Psychology) spent ten weeks doing a data-driven investigation of the relationship between mental health training of law enforcement officers and key outcomes such as incarceration, recidivism, and referrals for treatment. They worked closely with the Crisis Intervention Team, and they used jail data provided...
Kelsey Sumner, EvAnth and Global Health major and Christopher Hong, CompSci/ECE major, spent ten weeks analyzing high-dimensional microRNA data taken from patients with viral and/or bacterial conditions. They worked closely with the medical faculty and practitioners who generated the data. Project Results The team used statistics and machine learning to distinguish between viral...
MISTRAL is an NSF funded project for capturing and analyzing network data for research lab environments. A team of students will work with the MISTRAL team and members of the Duke University IT Security Office (ITSO), as well as a Code+ team, to analyze and develop methods for detecting network...
Students will coordinate with the Organisation for Economic Co-operation and Development (OECD) Working Party on Bio-, Nano-, and Converging Technology to develop a governance framework to both encourage the development of and mitigate the potential harms of emerging technologies. Framework development will require creative and interdisciplinary research to identify different dimensions of risks posed...
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...
The goal of this Data+ project is to apply and extend custom analytics solutions to understand and predict microbial population growth.An explosion of data has resulted from tracking the growth of bacteria in high throughput devices. These data were generated to understand how microbes grow. Better models that fit and...
Led by researchers from Duke University and Duke Kunshan University, a team of students will embark on an interdisciplinary research journey to explore the dynamic intersection of environmental science and machine learning, engaging in the recognition of wetland plant species through the analysis of satellite image time series. Students will...
A team of students led by researchers in the Hickey Lab in Biomedical Engineering at Duke University will develop computer-based simulations to understand how influenza spreads through human lung tissue and how the immune system controls infection. Using real biological images and data from influenza-infected lungs, students will build interactive...
This data expedition examined the musical concepts of pitch and rhythm. Pitch is the quality that makes it possible to judge sounds as “higher” and “lower” in the sense associated with musical melodies. Rhythm is the placement of sounds in time and in regular repeated patterns. For slow things, our...
Angelo Bonomi (Chemistry), Remy Kassem (ECE, Math), and Han (Alessandra) Zhang (Biology, CompSci) spent ten weeks analyzing data from social networks for communities of people facing chronic conditions. The social network data, provided by MyHealth Teams, contained information shared by community members about their diagnoses, symptoms, co-morbidities, treatments, and details about each treatment. Project Results: The team performed extensive data cleaning,...
Emily Horn (Public Policy, Global Health), Aasha Reddy (Economics), and Shanchao Wang (Masters Economics) spent ten weeks working with data from the National Asset Scorecard for Communities of Color (NASCC), an ongoing survey project that gathers information about asset and debt of households at a detailed racial and national origin level. They...
Introduce NBA and MLB datasets to undergraduates to help them gain expertise in exploratory data analysis, data visualization, statistical inference, and predictive modeling. Graduate students: Joe Futoma and Ken McAlinn, PhD students, Statistical Science Faculty instructor: Mine Cetinkaya-Rundel Course: STA 112 (Data Science) Applications: Assessing home field advantage Determining long...
Artem Streltsov (Masters Economics) and IIT Mechanical Engineering major Vinod Ramakrishnan spent ten weeks exploring North Carolina state budget documents. Working closely with the Budget and Tax Center, part of the North Carolina Justice Center, their goal was to help build a keystone tool that can be used for analysis of the state budget as well as...
How does human habitation relate to patterns in the natural environment? How do species respond to the presence of, and changes in, habitation? In this Data Expedition, students make use of public datasets from the Census and the Global Biodiversity Information Facility to examine relationships between individual species and human...
In light of Duke’s reopening amidst the COVID-19 pandemic, this project aims to track the movement of foot traffic in and around Bryan Center by analyzing Wifi log data from all users connected to wireless networks in the center during February 2020. Our team employed Markov Chains, Kernel Density Estimations,...
Bernice Meja (Philosophy, Physics), Jessica Yang (Computer Science, ECE), and Tracey Chen (Computer Science, Mechanical Engineering) spent ten weeks building methods for Duke’s Office of Information Technology (OIT) to better understand information arising from “smart” (IoT) devices on campus. Working with data provided by an IoT testbed set up by OIT professionals, the team used a mixture...
This Data Expedition introduces students to network tools and approaches and invites students to consider the relationship(s) between social networks and social imaginaries. Using foundation-funding data that was collected from the The Foundation Directory Online, the Data Expedition enables students to visualize and explore the relationship between networks, social imaginaries, and...
This project aims to improve the computational efficiency of signal operations, e.g., sampling and multiplying signals. We design machine learning-based signal processing modules that use an adaptive sampling strategy and interpolation to generate a good approximation of the exact output. While ensuring a low error level, improvements in computational efficiency...
Showing 241-260 of 388 results