Student Quotes

I want to emphasize how particularly crucial it was for someone like me, with limited prior access to this kind of hands-on, collaborative research. The program has given me what self-study never could: a clear purpose, the chance to learn by doing, and the opportunity to collaborate with amazing people. Working on this project with excellent teammates taught me what the workflow of a research project is like and honed my communication skills. Most importantly, it prepared me for my future academic pursuits by teaching me how to face complex, non-linear problems with persistence, and how to move forward with calmness and determination even when expected insights don’t appear, qualities I will carry with me always.

Zhiliang Hu, Durham Tech Community College
Data Networks of Asian American Literature, 1974-2024

Our team got to pick things we were interested in with a Sanford dataset containing four cohorts of high school students all over North Carolina public and charter schools. We had longitudinal student data so we could track the same students over several years. My research question was, How did Covid-19 affect students’ GPA and standardized test trajectories? I gained a lot of technical skills and did time-consuming data cleaning, which was worth it.

Adam Cartwright
Educational Trajectories in North Carolina

I find AI very interesting. When you work in this field you must get very deep, and I got a lot out of this project.

Yasir Alhasaniyyah (KAUST)
AI-Powered Discovery of Counterexamples in Discrete Mathematics

I have gained insight and practice in a lot of important fields, such as working in a team setting, building a project that can be applicable in the real world, and understanding the importance of meeting and adhering to your specific parts of the project and meeting deadlines. Entering data plus, I didn’t really think much about engagement and working together. Afterwards, I came out with a new understanding and confidence to work in a team setting and building projects too. I learned a lot about how data science and machine learning could be tied to my interest in ecology and also realized that the techniques learned here could have been applied to make my past projects more efficient. I feel like I’ve gained an important tool that will help me explore how deep learning can be used to support future projects involving data science.

Anonymous

When I first joined the program, I knew very little about data science and computational work, but after participating in group research for a few weeks, I became comfortable with a few key terms. I’ve improved my ability to work with real-world datasets, analyze outcomes effectively, and communicate technical work to different audiences. One of the most valuable parts of this experience has been working as a team. My teammates were supportive, curious, and eager to learn, which helped us overcome challenges and share ideas, strengthening our team bonds. In addition to technical skills, I have gained a deeper understanding of the process of conducting interdisciplinary research.

Anonymous

I gained valuable experience tackling real-world data science and machine learning challenges faced by companies in the industry. My project gave me exposure to both the technical and business sides of the work. I also had the opportunity to collaborate with a great team and build meaningful connections.

Anonymous

I’ve learned how to work in professional and group settings on data motivated projects. I’ve also learned how to use Python and its various packages to create data visualizations, filtering, etc.

Anonymous

Data+ made me realize how diverse data science work can be. Initially, I thought my project will be given a dataset and do certain analysis using regression models. But it turned out to be a project democratizing data analysis to biologists using a webapp, which involves a lot of front-end coding that I was not expecting. Through this I learned a lot about different aspects of the field.

James Peng
Predicting microbial growth to understand biological resilience 2025

I gained a lot from my Data+ experience. I learned how to work on the fly. How to work with students that are much different from myself with different upbringings and scientific backgrounds. I also learned how to stay resilient in the face of tragedy, adversity and a busy schedule to still get things done and get something meaningful out of the Data + experience. I think I doubted how much of a full and immersive experience it (Data +) would actually be. I was pleasantly surprised to find that, if given the right group and the correct project this experience could be just as meaningful as any summer internship or research opportunity at a company or even more so.

Uzo Uwazurike
Predicting microbial growth to understand biological resilience 2025

Through the Data+ program, I gained hands-on experience working with real-world healthcare data and deepened my understanding of the research process. I improved my coding skills in R and SQL, learned how to clean and analyze large datasets, and collaborated with a team to investigate a shared question. The program helped me grow both technically and intellectually, showing me how data science can be used to generate impactful, and human-centered insights.

Anonymous

Being part of the Data+ program taught me a lot. I learned how to work with data, clean it properly, and try out different machine learning models to find the one that works best. I also got to explore natural language processing and analysis. More than anything, it gave me real, hands on experience and helped me understand how data projects work in practice.

Rawan Albarakati
A Textual Analysis of Agricultural Research

I’ve come to realize that learning by doing, especially within a collaborative project, deepens not just my technical knowledge, but also my understanding of why certain concepts matter, especially abstract or theoretical ones and how can I apply them. Also, the experience sharpened my communication skills. I’ve come to see how essential clear articulation, feedback loops, and shared understanding are, often more so than technical ability, when working in a team. This was my first experience participating in a real project. I’ve gained insight into what it takes to build and sustain a project, like how goals evolve, and how unexpected problems arise, how crucial structure and iteration are to the process. Most importantly, I used to think a good idea would lead to a clear answer. Now I know that failure, ambiguity, and rethinking are the real core of research—and that frustration is part of the process, not a flaw.

Anonymous

I’ve learned skills in data collection, analysis, reporting, and visualization – all of which will serve me in any future research and my career. I also appreciated working in a team, the support from our project manager, and working to overcome obstacles together.

Josefina Masjuan
Building Stronger Communities: The Evolution of Funding in North Carolina Public Education

Participating in the Data+ program helped me build valuable technical and professional skills. I gained hands-on experience using R for data cleaning, visualization, and analysis, and became more comfortable applying statistical methods to real-world datasets. I also strengthened my ability to collaborate in an interdisciplinary team, stay organized while juggling multiple tasks, and take initiative by contributing new ideas and perspectives. Initially, I expected to simply complete tasks that were assigned to me, but this project encouraged me to explore my own curiosities and take a more active role in shaping our analyses. I realized that data science research isn’t just about following instructions—it’s also about asking meaningful questions, thinking critically, and contributing original ideas.

Johnathan Ross
Linking & Analyzing Data on Deaths in US Prisons

I was interested in Data+ to gain more exposure to research methods and coding; now at the end of the program, I feel like I’ve gained so much more. I leave this summer with great friendships and memories throughout the 10 week period. I’ve furthered my skills in presenting, research, data analysis, and problem solving.

Angelie Quimbo
Building Stronger Communities: The Evolution of Funding in North Carolina Public Education

I feel like I’m more skilled about processing data, especially I am more sensitive to the data distribution and could come up with statistical method to solve this quickly. Another big gain for me is I learn to present well in front of people.

Zini Yang
Building honeypots to track AI web scrapers

Before participating, I thought data science research was mostly a solitary, technical process, just coding and analyzing data behind a computer. But through Data+, I realized how collaborative and interdisciplinary it really is.

It changed my perception by showing me that the work was more collaborative than I initially expected. I also found myself genuinely excited during the research process, what I thought might be repetitive turned out to be full of new challenges and discoveries.

Maan Adam
Forecasting heavy rainfall in the southeastern U.S. using deep learning (Climate+)

I learned a lot about how data science and machine learning could be tied to my interest in ecology and also realized that the techniques learned here could have been applied to make my past projects more efficient. I feel like I’ve gained an important tool that will help me explore how deep learning can be used to support future projects involving data science.

Boyu Tan
Tracking Aquatic Insect Emergence Using Machine Learning (Climate+)

I have gained insight and practice in a lot of important fields, such as working in a team setting, building a project that can be applicable in the real world, and understanding the importance of meeting and adhering to your specific parts of the project and meeting deadlines. Entering Data+, I didn’t really think much about engagement and working together. Afterwards, I came out with a new understanding and confidence to work in a team setting and build projects too.

James Xiao
Building honeypots to track AI web scrapers

The Data+ program has reshaped my perception of Data Science research by highlighting the importance of collaboration, communication, and problem-solving within a team. Working on real-world projects showed me that while the work might be about numbers and algorithms for us, it can be life-changing for those impacted. This experience has broadened my understanding, revealing that data science is a dynamic and interdisciplinary field requiring a blend of technical skills, teamwork, and strategic thinking. Participating in the Data+ program has significantly enhanced my data analysis skills, particularly with tools like Python and GIS. It has also improved my ability to collaborate and communicate within a team, as we regularly presented our findings and received feedback. Additionally, I’ve gained valuable industry insights through required talks and sessions, learned best practices from mentors, and expanded my professional network. All these experiences have greatly boosted my career prospects in data science.

Samundra Adhikari, ’27
Energy transition during energy crisis: Cape Town’s experience

I feel more comfortable discussing work with a client and tailoring my project to meet their expectations. I also learned to work collaboratively in groups and to present my findings to an audience at a comprehensible level. I now understand that research is needed even for publicly available data because of the technical knowledge needed to understand the results. I will no longer assume that just because records are open to the general public that they are truly accessible.

Anon

I gained a lot of knowledge about working in data science and what is involved with gathering more accurate data. I enjoyed collaborating with other students within different majors to reach our goal of putting together a website with a focus on education.

Ocir Black, ’27
Mapping the Rosenwald Schools and their Impact on the Black Belt Region of North Carolina

Participating in the Data+ program has been an incredibly enriching experience, especially in terms of teamwork. Being part of a multidisciplinary team allowed me to gain insights from different perspectives. This exposure has broadened my understanding of different approaches to problem solving and enriched my overall learning experience. Data+ has changed my perception of data science research. The Ethics in Research course taken prior to the program highlighted the importance of data privacy, informed consent, and bias mitigation, and made me more aware of the ethical responsibilities involved. This experience underscored the need for integrity and ethical standards in all aspects of data science.

Ofosu Osei, ’27
Mastery Learning Data to Predict Course Performance

I have gained a lot of technical experience and feel I am better equipped to talk about my project and what I learned from it in the interview process for future internships.

Carlie Scheer, ’27
Analyzing Basketball Plays Using Computer Vision

I think I gained incredible professional skills on how to conduct myself in an internship-like experience within a team project. I also learned so many technical skills. The emphasis really seemed to be on growth rather than producing a deliverable, which made this perfect for my first summer at Duke!

Manahil Tariq, ’27
MISTRAL: Dynamic data analysis of security threats within research environments

First research experience – learned coding languages like Javascript, HTML, MYSQL, Flask in Python.

Anonymous

Coming into data science research, I had no clue about what it even was. The Data+ program taught me that it requires a great deal of patience, teamwork, and a strong foundation of knowledge. Participating in the program enriched my skills in teamwork and patience, while also deepening my expertise in Python, specifically with TensorFlow, Keras, PyTorch, and MNE. I honed my general coding abilities, developed proficiency in creating graphs using Matplotlib, and gained a thorough understanding of the data research process. I am very grateful for Data+, my colleagues, and all the knowledge I gained.

Darrick Zhang, ’27
Exploring novel machine learning techniques for Brain Computer Interface (BCI) applications

I have gained the needed perspective of how to combine a social science/humanities topic with computational methodologies. I believe this interdisciplinary perspective is very much important and needed in these years, and I hope this program could be offered more to help students gain this very applicable and malleable experience. I would recommend other people, regardless of their background, to participate in Data+.

Zhihui Zhou, ’27
Ethical Consumption Before Capitalism

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

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
Optimizing Hospital Scheduling Through Machine Learning

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

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

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 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 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 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

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+)

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 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.

Anonymous

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.

Helen Chen, Statistics ‘23
AI in the Investment Office

I didn’t really know how data science research applied to social science, but Data+ showed me that it can be a really successful avenue for discovery and change.

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

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 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 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

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

I learned there’s much more to it then looking at data. It’s also a way of thinking and organizing what you have analyzed to help others who aren’t able to look at data in such a way to understand it. It’s also a bit of storytelling in a way.

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

What I have discovered is that a majority of data research is about communication. How you interact with your teammates and superiors is just as important, if not more important, than being a genius in your field.

Andrew Scofield, Computer Science ’22, Birmingham-Southern College
For love of greed: tracing the early history of consumer culture

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

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

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

My group has been focused on cybersecurity and automation methods to prevent and seek out attackers to keep Duke websites and accounts from being compromised. I have learned a lot about cybersecurity, a field that I otherwise might not have pursued. It has been a very interesting and enlightening experience so far and I am excited to continue learning from the Duke OIT staff.

John Taylor, Computer Science ‘21
Applying Security Orchestration, Automation & Response (SOAR) to security threat hunting with Duke’s ITSO

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.

Benjamin Williams, ECE ‘21
ABOUT-US – A BOundary Update Tool for Utility Services

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.

Anonymous

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.

Anonymous

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.

Lucia Jones, Environmental Studies Brown University, ’20
When Black Stories Go Global: Analyzing the Translation of African-American Literature and Film

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.

Nathan Warren, MIDS, ’20
Human Activity Recognition using Physiological Data from Wearables

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.

Anna Zolotor, Undeclared, ’20
Piloting an Environmental Public Health Tracking Tool for North Carolina