Unlocking the Power of Data Science in Human Behavior: Your Capstone Journey
Welcome to an Exciting Challenge!
If you’re starting your Master’s in Data Science in Human Behavior, you’re in for a transformative experience. This program isn’t just about crunching numbers—it’s about using data to understand, predict, and improve human experiences across a wide range of fields. And one of the most thrilling parts of your journey? The Capstone Project.
What is the Capstone Project?
The capstone is your chance to apply everything you’ve learned to a real-world problem. You’ll work with cutting-edge data, apply machine learning and statistical techniques, and collaborate with researchers, organizations, and industry leaders to develop solutions that can make a meaningful impact.
The Impact of Capstone Projects
Past capstone projects have tackled critical issues such as:
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Equity in Science Publications – Analyzing gender imbalance in scientific authorship and citations, using an API to extract demographic data from journals.
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Neural Fingerprints in Object Recognition – Investigating how different individuals associate meaning with the same object by analyzing fMRI brain activity.
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Total Well-Being in Singapore – Improving elderly healthcare by developing a more efficient digital survey system to assess fall risks and other health concerns.
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Law for Learners Data Innovation – Streamlining legal aid for students by developing a Power BI dashboard and predictive modeling for better case routing.
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Healthy Minds App Engagement – Analyzing user behavior in a well-being app, defining engagement metrics, and identifying pathways for habit formation.
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Addiction Recovery Prediction – Using machine learning to predict substance relapse risk based on geolocation, stress levels, and social interactions.
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Unlocking Learning Insights with Canvas Data – Identifying student success patterns using educational data from an online learning platform.
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Impact of Research Participation on Student Learning – Exploring how engaging in research studies affects cognitive and personality traits, particularly for students with ADHD.
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Climate Change and Insurance Risk Analysis – Investigating the impact of extreme weather events on insurance premiums using publicly available data.
These projects showcase the diverse applications of data science in research, healthcare, education, social good, and industry! Let me know if you’d like me to expand on any of them.
Why This Matters
These projects aren’t just academic exercises—they drive real-world change. Whether you’re passionate about healthcare, psychology, education, or ethics in AI, the capstone allows you to shape the future with your insights. The skills you learn during your capstone will be the transferable skills that will support your next chapter – whether that be in industry, non-profit, or academia. In data science, there will always be new skills to learn, our students say that they are confident whatever the next tool to learn is, that they can learn anything in 3 weeks.
What You Can Expect
- Hands-on Experience – Work with large datasets, conduct experiments, and build predictive models.
- Interdisciplinary Collaboration – Engage with psychologists, educators, healthcare professionals, and tech experts.
- Innovation & Creativity – Solve problems in ways that haven’t been done before.
- Supportive Mentoring – Each capstone project has a dedicated mentor to support learning.
- Professional Growth – Gain valuable skills that will prepare you for careers in research, industry, or policy-making.
How to Make the Most of Your Capstone
- Follow Your Passion – Pick a topic that excites you. The best projects come from genuine curiosity!
- Use Your Resources – Faculty mentors, peers, and industry partners are there to help.
- Think Big, but Stay Focused – While innovation is key, defining clear goals will keep you on track.
- Be Open to Surprises – Data can lead you in unexpected directions—embrace the journey!
- Communicate Your Findings – The impact of your work depends on how well you share your insights with others.
Ready to Get Started?
Your capstone project is a chance to make a difference—not just in the academic world, but in real people’s lives. As you step into this challenge, remember: this is your opportunity to turn data into meaningful action.
So, what problem do YOU want to solve? 🚀
Fall 2024 Capstone Projects
Graduating class of 2024 after they presented their final capstone presentations!
Watch this capstone project overview with Caitlin Roa: Fall ’24 Capstone Project Overview
Fall 2023 Capstone Projects
For their capstone project, Sizhe Gao, Yanxue Ma, Lucas Modahl, and Yan Zhu partnered with Healthy Minds Innovations (HMI), a non-profit that provides tools for supporting healthy mental habits and cultivates the skills of well-being. The team worked together to create a central, standardized, documented database that encompasses all of HMI’s data in a single resource, properly cleaned, synchronized, and merged, with a pipeline for easily integrating/adding new data, with integrated tools for different audiences (clients, researchers, etc.) to be able to access and visualize results. This group was mentored by Tammi Kral, Behavioral Scientist at HMI; Caitlin Roa, Scientist mentor for the program; Ivette Colon, PhD mentor for the program.
“Being part of this program has been a remarkable journey of skill development and practical application, especially through the capstone project.” said graduate student Yuanxue Ma, “I’m particularly proud of the Power BI dashboard I created for data visualization. This project for me was more than just a technical exercise; it was a great opportunity to engage with real-world data and apply my learnings in a meaningful context. I look forward to bringing this invaluable knowledge and skills into my next adventure in the field.”
A second group of graduate students (Alex Cheung, Lihao Hou, and Zhuolon Zhong) conducted research on humor data. With their development of a prototype system that allows users to interact with an AI “humor assistant,” Cheung, Hou, and Zhong enabled users to explore and visualize data from prior New Yorker caption contests, interact with the AI assistant to develop their own caption ideas, and even predict human ratings of caption ideas. This group was mentored by Tim Rogers, Faculty mentor for the program; Siddharth “Sid” Suresh, PhD mentor for the program; Kushin Mukherjee, PhD mentor for the program.
“Our aim was to create a tool that uses data science to help people develop their creativity, and allow scientists to explore/understand creativity, using the cartoon caption contest as an example domain,” the students wrote. “We hope these activities provide a useful foundation for understanding how science can be used to enhance abilities in this uniquely human domain, as well as some tools for studying this poorly understood aspect of human cognition.”
Finally, in partnership with Embark Behavioral Health, a nationwide network of outpatient centers and residential programs offering mental health treatment for preteens, teens, and young adults, graduate student Drew Beatty set out to analyze program outcomes and provide recommendations to clinicians and stakeholders. Over one semester, Beatty produced several analytical reports using Specialty Program clinical data, gave a new lens for visualizing and conceptualizing metrics related to client wellbeing, and developed a Clinical Index report which will be used for program assessment, with the overall goal of improving treatment quality; client, parent, and staff experiences; and on campus safety and staffing.
“These deliverables were received very favorably by all stakeholders,” wrote Embark’s leadership team, “and we are extremely grateful for Drew’s excellent dedication to her projects.”
Capstone Process
The first fall semester students are exposed to many different aspects of examining data. We invite guest speakers to the proseminar (psych 709) from industry, non-profit, government and academia to share the kinds of data that they work with and the challenges they tackle. As students are developing skills in programming (psych 750) and statistical analysis (psych 610), we begin to discuss data wrangling and cleaning and how to apply those skills to real-world data.
In the spring semester students begin to explore several mini-projects, this is an opportunity to learn new skills, work with a team, figure out what sparks interest and what skills still need to be developed. Professional development goals for this semester include: project management, team roles, creating timelines for deliverables, effective presentations and data vizualizations. Students incorporate their newly aquired applied machine learning (psych 752) and advanced statistics (psych 710) skills into their data analysis mini-projects. By the end of the spring semester students will rank their interests and importance of certain aspects of their capstone project: working in industry/government/research; working on a certain topic; working on a certain skillset. Students teams are mentored by faculty, sponsor, scientists, PhD students, and peer mentors. On occation a student might seek an independent project, while we do allow this, we also ask that they meet weekly with a team that is working on a similar project so that they can share insights and solve puzzles together. A great deal of learning happens in these meetings and in converations with data scientists that are all trained differently and can learn from each other.
The plan for the summer is that students will spend 15 hours/week learning the skills needed to complete the deliverables for the fall capstone project. Student teams work together and delve into real data, spending time cleaning, understanding data structures and information architecture, and getting comfortable with analyzing and exploring insights. By the end of the summer, students will create a statement of purpose for the fall semester and meet with the capstone sponsor (industry partner) to present what they have learned and a couple directions for where they could go. Then we get sponsor feedback on their priorities. The sponsor can meet weekly, biweekly, or monthly with the student team based on interest and availability.