AI-Assisted Qualitative Codebook Generation: A Collaborative Research Initiative Between the Ohio State University and Inje University

Qualitative research offers social scientists a powerful lens for understanding human experience, but it does not scale easily. Analyzing dozens of in-depth interviews by hand is slow, labor-intensive, and difficult to keep consistent across a large dataset. This research initiative, led by Dr. Joyce Y. Lee, Associate Professor and Director of the Child and Family Wellbeing Laboratory at The Ohio State University College of Social Work, addresses that challenge directly through an international collaboration with SCLAb, IDA, Inje University in Gimhae, South Korea. 

The study at the center of this work examines the political, social, and family lives of Trump-supporting fathers in America. Through 32 in-depth interviews, the research team explored three core domains: political decision-making and voting motivations, perspectives on masculinity and gender roles, and experiences of fatherhood and family life. These interviews generated rich, complex qualitative data, precisely the kind that yields the deepest insights but demands the most analytical effort to process.

A research collaboration between the University of Florida, USA, and Inje University, South Korea, focuses on Remaining Useful Life (RUL) analysis using AI-driven approaches. The research is led by Prof. Nam Ho Kim from Department of Mechanical Engineering, University of Florida, United States of America and Prof. Hee-Cheol Kim with Dr. Arif serving as co-lead from SCLab, Department of Digital Anti-Aging Healthcare, Inje University, Republic of Korea. The collaboration aims to develop advanced predictive models for accurate RUL estimation and intelligent predictive maintenance. 

Sustainable AI for Healthcare 4.0 

A collaborative research initiative between SCLab, Institute of Digital Anti-Aging Healthcare (IDA), Inje University, South Korea, and Kalinga Institute of Industrial Technology (KIIT), India, will focus on “AI-Driven Sustainable Healthcare for Industry 4.0.” The collaboration aims to develop intelligent and data-driven approaches for optimizing healthcare supply chains, improving resource efficiency, reducing waste, and enhancing sustainability. By integrating AI with Industry 4.0 technologies, the research will contribute to smarter, more resilient, and sustainable healthcare systems.