Data+ is a full-time 10-week summer research experience that welcomes undergraduate and masters students interested in exploring new data-driven approaches to interdisciplinary challenges. It is suitable for students from all class years and from all majors.
Students join small project teams (at most 3 undergrads and 1 master’s student per team), working alongside other teams in a communal environment. They learn how to marshal, analyze, and visualize data, while gaining broad exposure to the modern world of data science. The projects come from an extremely diverse set of subject areas. It is our hope that students will be able to both work deeply into their specific project and get a very broad picture of most of the skills needed for modern data science.
Participants will receive a $5,000 stipend, out of which they must arrange their own housing and travel. Funding and infrastructure support are provided by a wide range of departments, schools, and initiatives from across Duke University, as well as by outside industry and community partners.
Data+ has returned to 100% in-person participation. Participants may not accept employment or take classes during the program; this requirement is strictly enforced and non-negotiable.
Due to the nature of the data involved in some of the projects, human subjects research training will be required of all participants and will be provided after admission to the program. With each project, we have attempted to list potential majors and/or interests that might be most interested in the project, but these should not be seen as requirements in any way! Quantitative STEM majors like mathematics, computer science, statistics, and electrical engineering are relevant to all.
Now accepting Project Proposals for Summer 2024!
For more information on how to submit a proposal, see our request for proposals (PDF).
Student applications will open in late December, stay tuned for our announcement!
Industry partners are essential to Data+. Learn how to become a partner.
From Our Data+ Students
I thought it would be a bunch of number computing, but it actually thought me a lot about presenting data in a community of collaborators in an effective manner.
Isabela Agi Maluli, Chemistry and Psychology ’25
Hip Hop Pedagogies & Education for Citizenship in Brazil & the US
I have gained a lot of knowledge in the field of natural language processing, and I would like to learn more about NLP and ML.
Nikki Daga, Computer Science and Statistics ‘26
Machine Learning and Evaluating Technical Documentation
I learned a lot more about data wrangling, and using resources other than Duke to help me gain knowledge about R and general programming practices. It felt more like a real job than a class-based curriculum, with actual deadlines and meetings where we had deliverables. It made me learn what it could mean to be a data scientist in the workplace one day.
Avery Hodges, Statistical Science ‘23
Data Science for Operations and Planning at Durham Public Schools
I gained a lot of practical experience working on a research project that I’m interested in. I’ve learned that I enjoy doing this sort of work. I developed lots of python skills regarding running machine learning models, image processing, file management, and desktop app development. My mental image when thinking “data science” is having a lot of data in columns, running a regression on it, and visualizing that. Our project was more image-processing oriented, so it expanded my perception of what “data science” can mean. Other groups also were working on things that weren’t the typical model-patterns-in-data workflow.
Adam Kosinski, Computer Science ‘24
Innovations in Research Technology to Assess Forest Wildlife (Climate+)
Initially I thought data science would be a very rigid, monotonous “working with data” field. Going to all the talks opened my eyes to how data science can be applied to all sorts of tasks and fields, from pure data analysis to environmental monitoring! I learned how to work as a team on a CS / data science project. Also exposed to how data science can be applied to a variety of tasks and fields. Definitely gained connections and experience relating to data and computer sciences.
Eric Lee, Computer Science ‘26
ML for high complexity clinical HLA datasets
I was able to move a project that I had been working on in the semester closer to publication. I gained experience in independent work and motivating a team. I learned about many techniques that I was unaware of through the program talks, and I also now think of data scientists more as data communicators.
Julia Leeman, Neuroscience and Music ‘24
Auditory Imagery of Speech and Non-Speech Sounds
I had no idea what data science even was before this program, but I’ve gained a strong knowledge of R and a grasp of data science research processes.
Will Leiber, Linguistics ‘25
Mental Health and the Justice System in Durham County
I’ve learned so much about statistical analysis and dashboard development. Data+ gave me a great experience working with a team, and I learned so much about collaboration and leadership in working with others.
Cynthia Ma, Computer Science ‘26
Visualizing data to increase access to diapers
I have learned how to use a new software tool (MATLAB) to manipulate audio and video data, I have also learned how to work efficiently in a team, and the process of starting a data science project from scratch.
Damilola Oshunyinka, NCCU, Pharmaceutical Sciences ‘23
Strengthening Partnerships: Durham Schools & Local Universities
Collaborating in a group and learning to work with my project manager and project lead has been a great experience. This was one of my first times working on a project without a ton of structure, so it was very valuable to learn how to direct myself and where to look for help when stuck. Before Data+, I hadn’t considered the research part of Data Science but I have gained an appreciation for the background work that goes into Data Science, such as finding articles or other research to guide my own research. The panels also showed me that Data Science is a wide field and there are a large amount of professions that use Data Science in their everyday life.
Grady Purcell, Statistical Science ‘26
Using Deep Event-Level Data to Provide Quantitative Insights for Duke Women’s Soccer Team
I have gained valuable project group experience, working on a real project that affects real people. Not only have I gained many important technical skills but also important skills about working in a team and communicating findings, which I believe to be most important. I learned that the most important aspect of data science research is actually communicating your results. Discovering great findings is great, but totally useless if one does not know how to communicate those findings to a greater audience.
Dillan Sant, Statistics ‘25
Data Science for Operations and Planning at Durham Public Schools
As someone who hasn’t done data science or programming in the past, I have learned a lot about coding and computers in general, especially when using Python. The program made me realize that real data can often be messy, and it taught me how to communicate with my teammates and stakeholders to get the best results.
Bo Schaffer, Neuroscience ‘26
Developing Impact Assessment Tools for Neurotechnologies
I enjoyed hearing the other groups presentations that seemed they were solving big issues. The talks with alumni from different major and paths was helpful, good to know there are different uses for data science. breakfast was delicious on Wednesdays, and I liked that there was care put into cultivating ‘soft’ skills like presentations – Paul had a nice speech about that on the first day, that a data scientist that can’t present results to non-technical people are not useful.
Data+ by the Numbers
weeks during the summer
undergraduates per team
grad student mentors per team
projects sharing ideas and code
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