Data+ is a full-time ten week summer research experience that welcomes Duke 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 masters 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 (see below) come from an extremely diverse set of subject areas.i 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+ is typically a program where students have dedicated workspace within Gross Hall at Duke University. For the last two summers (2020 and 2021), Data+ ran entirely remotely due to the pandemic, and was quite successful. We are back to in-person for summer 2022!
From Our Data+ Students
Jessica Ho, Math and Neuroscience ‘22
Predicting Baseball Players’ Athletic Performance Utilizing Baseline Assessments of Vision
Nick Datto, Neuroscience, Computer Science, and Cultural Anthropology ‘23
Race and Housing in Durham over the Course of the 20th Century
I’ve learned how interdisciplinary data science is, and how a team of people with many different academic trajectories can work together on the same project, something that I don't think happens very often in other areas.
I had expected it to be very analytical, but I was surprised at the creativity that was also required. I enjoyed this aspect a lot.
I've gained a lot of valuable insight into the career fields of environmental health and epidemiology. I've also learned a lot about project workflow and how to work through the different phases of a long term project with a team. In addition, my skills in R coding and Tableau have improved a ton.
I have gained so much knowledge and confidence! And it is not limited to the area of technology, although I have learned to code in R, navigate PACE, and so much more. I have better discovered the benefit of working with a team and received motivation and mentors by seeing female-identifying students, like myself, succeed. Hearing their success stories via panels or team meetings has given me so much more confidence as a young woman wanting to pursue a career in STEM.
Beyond solid technical machine learning skills, I've received a greater appreciation for data science as a tool to understand everything--from aircraft maintenance to the humanities. Before, I'd never expected that conducting humanities research would teach me how to wield and utilize the most cutting-edge research in machine learning and natural language processing. My team is using new package libraries and research papers written by lead researchers this year to conduct our analysis of ancient texts. In Data+, New meets Old.
Albert Sun, Computer Science and Public Policy ‘23
For love of greed: tracing the early history of consumer culture
Working remotely has made coordination much more difficult. However, we really have been embracing GitHub and box to overcome these challenges. I have learned a lot about RNNs and the applications of GRUs and LSTM's and how to implement such layers, in addition to learning how to use pytorch as previously I only used tensor flow.
It was difficult at first to jump into Data+, but doing this has benefited me a few ways. Having to learn Python on my own, in a very short amount of time, with almost no prior coding experience (I didn't even know what a package was) and quickly turning around and using those skills taught me that I am capable of flexibility and learning on the job. Coding also requires an immense amount of problem solving and independence. Although my mentors are fantastic, it's up to me to figure out where I want to take the project and how I want to do it. Data+ has been a really invaluable exercise in teamwork.
Ellen Mines, Biology and Philosophy ‘21
Computational Tools to Improve Healthy and Pleasurable Eating in Young Children
My coding skills and machine learning knowledge had a huge leap. I learned how to better work in a team as well.
I learned a lot about data science and using code to manipulate data. I learned how to properly use a terminal, deep learning/machine learning, pandas, and many other skills. Also, I gained collaboration skills when it comes to developing code.
I’ve learned to work through the entire process of a data science project, from assembling data sources all the way through presenting our findings. I’ve also developed insight into working in a team with people of different backgrounds and interests, which enabled us to contribute to the project in different ways. I’ve taken various lessons and hard skills that will carry with me into my future academic and professional endeavors.
Benjamin Chen, Computer Science, Economics ‘22
Protecting American Investors? Financial Advice from before the New Deal to the Birth of the Internet
Data+ absolutely changed my perception of data science research. Learning data science has been more intuitive than expected. There are also resources all over the Internet in addition to team members that are able to provide assistance when one is facing difficulty with an aspect of a project. Data science is also able to be applied to many more scenarios than I expected; I look forward to continuing data science research in the future.
I gained concrete skills in R and Tableau, the ability to collaborate in a virtual environment, and a better understanding of what data science actually means. I also got a glimpse into the public health field and got to learn what many different public health careers might actually entail.
I have gained a significant amount of knowledge of the cybersecurity industry and attack methods due to the nature of the background research I had to do for my project. In addition, I was able to apply my knowledge of statistical analysis to real data and learn new techniques to arrange data such as time series analysis.
Since I've never participated in research before, especially not research this independently oriented, the main thing I feel I've gained from this experience is confidence. I feel like I have a much better understanding of my own capabilities, and I honestly feel much less intimidated by the idea of pursuing research, not just in Data Science.
Donald Pepka, Math, Political Science, and Creative Writing ‘21
For love of greed: tracing the early history of consumer culture
I learned a number of hard skills in terms of coding languages as well as some soft skills along the lines of working with a team and coordinating with a client.
I definitely gained a lot of experience in R and in Tableau, but I also learned a ton about the fields of data science and public health. We had several interviews with community partners that helped me learn a lot about the different types of careers in data science, environmental advocacy, and environmental health.
Leah Roffman, Environmental Science ‘23
Piloting an Environmental Public Health Tracking Tool for North Carolina
I learned about team communication and organizational skills, time management, and I think I have a greater appreciation for how socio-cultural analysis from a humanities perspective can work in tandem with STEM based modes of collecting information/data.
Luci Jones, Environmental Studies Brown University
When Black Stories Go Global: Analyzing the Translation of African-American Literature and Film
Through the program, I not only developed my technical skills with regards to programming and data visualization, but I also learned a lot more about finance and the intersections of finance and data science. This program really incited my love for programming and problem-solving with data, and has made me even more interested in studying statistical science and data science at Duke. Finally, I learned how to effectively collaborate and communicate with a team in a virtual environment.
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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