Nick Datto, Neuroscience, Computer Science, and Cultural Anthropology ‘23
Race and Housing in Durham over the Course of the 20th Century

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.

Sydney Hunt, Engineering ‘23
Predicting Blindness in Duke’s Glaucoma Patient Population

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.

Pavani Jairam, Physics ‘23
Finding Space Junk with the World’s Biggest Telescopes

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.

Amber Potter, Computer Science ‘23
Predicting Baseball Players’ Athletic Performance Utilizing Baseline Assessments of Vision

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

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

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

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.

Matthew Feder, Computer Science ‘22
Applying Security Orchestration, Automation & Response (SOAR) to security threat hunting with Duke’s ITSO

Jessica Ho, Math and Neuroscience ‘22
Predicting Baseball Players’ Athletic Performance Utilizing Baseline Assessments of Vision

My coding skills and machine learning knowledge had a huge leap. I learned how to better work in a team as well.

Noah Lanier, Psychology ‘22
Human Activity Recognition using Physiological Data from Wearables

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.

Malik Scott, Global Health ‘22
Predicting Baseball Players’ Athletic Performance Utilizing Baseline Assessments of Vision