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Doctoral Candidate Tackles Social Issues Using Data Science

A personal tragedy inspired graduate student Felix Junior Appiah Kubi to apply his passion for data science to explore how machine learning can improve testing protocols and health-related decision making.

Felix Junior Appiah Kubi is a doctoral candidate at the University of Northern Colorado, where he has two semesters left. Growing up in Ghana, he was fascinated with mathematics and computing — a passion that led him to statistics and data science.

Today, as a doctoral candidate in UNC's Applied Statistics and Research Methods program, he's applying advanced statistical methods to address complex societal problems. Even before completing his dissertation, his research work has been validated through invitations to two data science gatherings, including a PyCon US 2024 conference and the highly competitive Data Science for Social Good program hosted by the University of Washington.

"Three strong interests that have been developing steadily for years are statistics, society and health. When I was in Ghana, I focused mostly on theoretical statistics, but at UNC, I've had opportunities for hands-on research and collaborations with experienced faculty members in diverse fields," Appiah Kubi explained.

Appiah Kubi is midway through his dissertation, "Adaptive Leveraged Causal Inference With an Application on PCR Testing," which seeks to optimize polymerase chain reaction (PCR) testing protocols and enhance health-related decision-making. Additionally, he conducted a significant study on cybersecurity. Both projects harness the power of machine learning, a subset of artificial intelligence, to achieve enhanced outcomes.

Felix Junior Appiah Kubi facing front.
Felix Junior Appiah Kubi

"We’re making headway in my dissertation by building a model and developing an algorithm that teaches the computer to learn from data. The technology will mimic human judgment to help us solve problems. It can learn, reason and make decisions," he said.

He's gathered data and is currently working on simulations for his dissertation, which he'll defend by August.

"Two years ago, my niece passed away because she was misdiagnosed. That inspired me to contribute to the health care setting," he shared.

Appiah Kubi works with Associate Professor Han Yu in the College of Education and Behavioral Sciences' Department of Applied Statistics and Research Methods.

"For the past two years, Dr. Yu has provided me with valuable insights and guidance in our work and throughout the research processes. His mentorship has enabled me to navigate complicated concepts and challenges in machine learning for functional data analysis," Appiah Kubi said.

Yu emphasized that while Appiah Kubi is still learning, his exceptional analytical skills in data science and the potential of his research to translate theoretical ideas into tangible, real-world applications make him stand out in the Ph.D. program.

"Felix's ability to grasp complex concepts quickly and apply them practically has been evident in his coursework and his research projects. He has a genuine interest and commitment to using data science for social impact, reflecting an understanding of the social issues at hand and a desire to make a positive difference," Yu remarked.

By applying state-of-the-art data science techniques to his cybersecurity and medical projects, Appiah Kubi is facilitating compelling and exciting discoveries while highlighting his research's practical impact.

"I have no doubt that Felix will make significant contributions to the field of statistics and data science," Yu said.

Appiah Kubi participated in a collaborative cybersecurity project with Assistant Professor Vivian Guetler from the College of Humanities and Social Sciences' Criminology and Criminal Justice department. Titled "Hacker Forum Topics and Networks: A Machine Learning and Qualitative Text Analysis Approach for Cybersecurity," they explored using machine learning and qualitative analyses to examine hacker forums. Their research identified key topics and knowledge-sharing practices among cybercriminals.

"Through a data-driven approach, we discovered the dissemination of hacking tools and techniques. The research shed light on the dynamics of cybercriminal communities and provided insights for improving cybersecurity measures," Appiah Kubi said.

PyCon US 2024, the largest U.S. annual gathering of Python programmers and enthusiasts, awarded Appiah Kubi a grant to attend this year's conference.

Additionally, he was selected as a 2024 fellow in the University of Washington's Data Science for Social Good summer program. During the program, 16 talented students from across the nation spend 10 weeks collaborating on data-driven projects aimed at tackling public health, environmental conservation and social justice challenges.

"I believe my team will investigate unsheltered homelessness in King County, Washington. At the end, we'll present our solution to county stakeholders. What I learn there potentially could be applied to Colorado," he said.

After he graduates, Appiah Kubi aspires to become a renowned statistician and data scientist.

"I look forward to contributing to the artificial intelligence field and making advancements that will benefit society," he said.

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