Champlain Research on Machine Learning & Data Science Gets Noticed

In today’s data-driven world, the ability to analyze large amounts of data is transforming industries, but with this progress has come new concerns around privacy. Computer Science & Innovation and Data Analytics double majors Mason Lee ’25 and Ness Campagna ’25 are addressing these critical concerns head-on, and their innovative solutions are getting global recognition! The two Division of Information Technology and Sciences students’ recently had their research paper accepted at the prestigious IEEE International Conference on Future Machine Learning and Data Science—one of the most respected platforms for cutting-edge technological advances.

A Breakthrough in Data Privacy Research

In “Enhanced Stratified Sampling: A Method for Privacy Preserving Big Data Publishing,” Lee and Campagna, working alongside their mentor Assistant Professor Vikas Thammanna Gowda, outline a groundbreaking new data analysis method called Enhanced Stratified Sampling (ESS).

The ESS technique builds on existing privacy-preserving frameworks (such as k-anonymity, l-diversity, and t-closeness) to better protect sensitive information without sacrificing the data’s analytical integrity or usability. Their research focuses on the delicate balance between preserving privacy and maintaining data usability—an increasingly critical issue in fields ranging from healthcare to finance.

“Privacy-preserving data publishing is about sharing useful information while protecting people’s private details,” explains Thammanna Gowda. For example, a school might share data about students’ grades to show trends, or a hospital might share data about diseases for research, but in both cases, they remove names and personal details so no one knows who the data belongs to. Techniques like adding small changes or grouping similar data help keep the information useful while protecting individual privacy.”

What Is the IEEE International Conference on Future Machine Learning and Data Science?

The Conference on Future Machine Learning and Data Science, being held November 20–23 in Sydney, Australia, is jointly organized by IEEE and Global Circle for Scientific, Technological and Management Research (GCSTMR). IEEE is a trusted global voice for engineering, computing, and technology information. The goal of the conference is to welcome young researchers and leading experts from around the world to share innovative research in the fields of Artificial Intelligence, Computer Vision, Future Machine Learning Technologies, and Data Science.

“Undergraduate research provides students with the opportunity to explore real-world problems, gain hands-on experience, and develop critical thinking and technical skills outside the classroom. Since publishing papers is usually associated with graduate-level work, undergraduates who contribute to publishable research stand out as strong candidates for graduate school or competitive careers,” says Thammanna Gowda. “This experience also allows them to connect with mentors, contribute to meaningful projects, and make a real impact in their field early in their academic journey.”

Programs that Push the Boundaries of What’s Possible

The recognition of Lee and Campagna’s work at the IEEE conference is a proud moment for our community and a clear indication that Champlain’s focus on experiential learning and academic excellence is paying off. This achievement is also a testament to the collaborative environment at Champlain, where faculty like Thammanna Gowda foster meaningful, hands-on learning experiences that prepare students to excel in the professional world.

As the fields of data science and computer science continue to grow, Champlain’s students aren’t just doing exemplary school work—they’re addressing real-world challenges and standing at the forefront of cutting-edge technological advancements.

“Programming has been a passion of mine for a long time now, and I love creating algorithms to solve problems. Having the chance to use what I’ve learned inside and outside of the classroom on something as applied and impactful as this has been a really fun experience. This is a team I’m really proud to be a part of,” says Lee.

Similarly, “I’ve always aspired to work on meaningful issues that impact people out in the real world, and getting this method published is a way of doing that,” says Campagna. “The opportunity to work on a project so technically advanced and have it be internationally recognized has definitely made me more confident within my field. I would love to continue my work in data science after graduation.”

We look forward to their continued success as they push the boundaries of what is possible in technology and data science. Congratulations to Lee, Campagna, and Thammanna Gowda for their incredible work, and thank you for representing Champlain College on the global stage.