This summer marks a new chapter for Bowdoin as the inaugural season of the Gomezgil Yaspik Data Science Laboratory gets underway. Founded by Assistant Professor of Digital and Computational Studies Vianney Gomezgil Yaspik, this Bowdoin data science lab represents a significant milestone for the college’s data science initiatives. It’s designed to give you—whether you’re a student or a researcher—a practical place to ask big questions and explore data-driven answers.
As part of the broader Bowdoin summer research efforts, the lab also opens doors for a new type of data science fellowship that emphasizes hands-on learning. This isn’t just about theory; it’s about building real projects with real datasets, all within a supportive academic environment.
Introducing the Gomezgil Yaspik Data Science Laboratory
That hands-on, project-focused approach is the foundation of the Gomezgil Yaspik Data Science Laboratory. This lab was founded by Assistant Professor of Digital and Computational Studies Vianney Gomezgil Yaspik, and it’s designed to give students from any major the practical tools they need to ask and answer big questions using data. Instead of reserving data science for computer science majors, the Bowdoin data science lab opens its doors to historians, biologists, economists, and artists alike.
The lab runs every summer, providing an intensive research experience that goes far beyond a typical classroom assignment. You get to work with real datasets, build actual projects, and learn by doing under close mentorship. The Bowdoin data science lab founder, Professor Gomezgil Yaspik, envisions data science as a versatile tool for every discipline, not just a specialty for programmers. That means if you’re studying sociology, environmental science, or literature, you can still dive into data analysis and find meaningful insights.
This lab is a key part of the broader data science program Bowdoin is building. It emphasizes collaboration across fields, so you’re not stuck in a silo. Instead, you learn how to frame questions, clean messy data, choose the right分析方法, and communicate your results clearly. Whether you’re analyzing historical trends or mapping ecological patterns, the Gomezgil Yaspik Data Science Laboratory gives you a reliable, step-by-step way to turn raw information into real understanding.
A Competitive Fellowship Program
The Gomezgil Yaspik Data Science Laboratory isn’t just a place to learn techniques—it’s also a launchpad for original research. This summer, the lab kicked off its first fellowship program, drawing interest from across the campus. More than twenty students applied for just five fellowships, making the selection process highly competitive. The 2026 cohort includes Cindy Dai, Grace Kinum, Kate Saccaro, Maddy Ohta, and Madina Sotvoldieva, representing majors in biology, economics, math, digital and computational studies, and computer science. This diversity highlights how the Bowdoin data science lab attracts talent from different fields, each bringing a unique perspective to data-driven questions.
Each fellow proposed an original research project, turning their curiosity into a structured investigation. To support this work, every student received a $7,000 Bowdoin fellowship plus a housing stipend, allowing them to focus entirely on their projects without financial distractions. This summer research stipend removes barriers, so you can spend your time digging into data rather than worrying about expenses. Whether you’re in biology, economics, or computer science, the program shows how the lab’s practical, step-by-step approach applies to real-world problems. The fellowship is a concrete example of how Bowdoin invests in student-led inquiry, giving you the resources to ask big questions and find clear answers.
A Summer of Structured Research and Collaboration
Fellows follow a rigorous daily schedule that balances independent work with collaborative learning. This structure is a key feature of the Bowdoin data science lab, ensuring you make steady progress while learning from peers and mentors.
Daily Routine and Mentorship
Each weekday morning, students gather in Mills Hall for group meetings and one-on-one sessions with Gomezgil Yaspik. This consistent routine helps you stay on track with your project, while the group setting encourages you to share challenges and solutions. It is a practical way to build momentum and avoid getting stuck on technical problems alone.
Advanced Workshops
Beyond daily mentorship, the program features advanced workshops taught by faculty from various departments. For example, Eric Chown covers cognitive research methods, Martin Abel teaches survey design, Adrianne Kinney introduces machine learning techniques, and Gomezgil Yaspik leads a session on advanced data science. These sessions give you exposure to different analytical tools and research approaches, making the Bowdoin summer research schedule both intensive and diverse. You gain hands-on experience with methods you might not encounter in a standard classroom setting.
Research Projects: Individual and Group
By summer’s end, each fellow completes an independent research paper and contributes to a group project with Randall Dick. This dual focus means you develop your own expertise while learning to collaborate on a larger question. One example is Cindy Dai, who is using data science to study the invasive tunicate Didemnum vexillum in the Gulf of Maine. Her project shows how the data science workshops Bowdoin offers can be applied to real ecological challenges. The structured routine, combined with expert-led workshops, ensures you leave the program with both a finished paper and practical teamwork skills.
Data Science Across Disciplines
That collaborative spirit is central to the lab’s broader mission. One of its core goals is to demonstrate that data science is not limited to computer science. Professor Gomezgil Yaspik envisions data science as a tool that can empower students in every discipline, not just those with a technical background. The 2025 cohort embodies that vision perfectly. This year’s fellows—Cindy Dai, Grace Kinum, Kate Saccaro, Maddy Ohta, and Madina Sotvoldieva—bring majors ranging from biology and economics to math, digital and computational studies, and computer science. This mix of backgrounds is intentional. It shows how interdisciplinary data science can work in practice.
You can read more on this topic in University of Victoria’s Upgraded Cloud Drives Research.
Consider Cindy Dai’s project as a prime example of data science in biology. She is using computational methods to study the invasive tunicate Didemnum vexillum in the Gulf of Maine. Instead of just manually cataloging specimens, she applies analytical techniques to understand how this species spreads and impacts local ecosystems. For you, this highlights a key takeaway: data science skills can transform how you approach research in nearly any field. Whether you are tracking invasive species, modeling economic trends, or analyzing historical texts, the underlying principles of data handling and pattern recognition remain the same. The lab provides the structured environment to learn those principles, regardless of your major.
The Lab’s Long-Term Vision for Data Science at Bowdoin
With a strong start, the lab aims to become a fixture in Bowdoin’s academic landscape. The inaugural season of the Gomezgil Yaspik Data Science Laboratory signals a new chapter for Bowdoin, moving data skills from a niche interest into a core part of the liberal arts toolkit. You can see that enthusiasm is already there: more than twenty students applied for the five fellowships. That level of interest tells you the Bowdoin data science lab is filling a real need on campus.
Looking ahead, the lab plans to keep expanding data science opportunities for all majors. The future of data science at Bowdoin isn’t just about computer science students. It’s about giving history majors, economics students, and everyone in between a practical way to work with data. The lab’s long-term vision includes more structured workshops, collaborative projects, and possibly a recurring summer program that becomes a tradition.
For Bowdoin data science lab growth, the key is making data skills accessible without watering them down. The lab wants to be a reliable resource where you can learn the fundamentals, test your ideas, and get feedback. Whether you’re analyzing survey results or building a model from scratch, the goal is to give you the confidence to ask bigger questions. That’s the real payoff: a lab that helps you see data as a tool for discovery, no matter what you study.
Frequently Asked Questions
How can you apply for the fellowship at the Bowdoin data science lab?
You submit an application during the spring semester, which includes a statement of interest and a brief project proposal. The selection committee looks for curiosity and a willingness to learn across disciplines, rather than a specific set of prerequisites. Accepted fellows then work closely with faculty mentors on real-world data challenges.
What distinguishes the Gomezgil Yaspik Data Science Laboratory from other academic labs?
Unlike many labs that focus on a single field, the Bowdoin data science lab intentionally brings together students from the humanities, social sciences, and natural sciences. This cross-disciplinary setup means you apply data science methods to questions as varied as invasive species ecology and sports analytics. The lab’s structure emphasizes hands-on collaboration over isolated research.
What kind of prior experience do you need to join the lab’s projects?
No advanced programming or statistics background is required to participate. The lab provides practical onboarding sessions and pair you with a mentor who guides you through the specific tools and techniques for your project. The key requirement is a genuine interest in asking big questions and using data to answer them.
