From Medicine to AI: Bridging Science and Technology

What if AI could bridge the gap between medicine and technology? This question has driven my journey across two continents, multiple disciplines, and 15 national research projects—shaping my expertise in medical AI.

I grew up in both South Korea and the U.S., experiencing two distinct cultures and education systems. While my professional journey has taken me across both countries, my family now lives in Seattle, Bellevue.

My passion for medical research began in high school when I came across a study on dementia in nuns from the University of Minnesota, Twin Cities. That one paper sparked my curiosity and led me to pursue biomedical research from Los Angeles to Minnesota.

🔹 University of Minnesota – Conducted leukemia research at the university hospital, focusing on Natural Killer Cells. My undergraduate thesis explored stem cell therapy for pediatric leukemia.
🔹 Coding from Biology to AI – I started coding at 20 while analyzing biological data. Over the years, it evolved from a tool into a passion, leading me from bioinformatics to AI-driven medical research.
🔹 Medical Internship & Career Shift – While working in clinical research, I realized my true interest lay in the technical aspects—data analysis, machine learning, and automation—rather than traditional medical practice.
🔹 PhD in Medical AI – I transitioned into AI research with a background in biomedical engineering, joining a government-funded research institute while pursuing my PhD. Unlike conventional PhD programs, my research was supervised by senior researchers rather than professors. The high turnover in government research institutions led to frequent changes in my advisors, as many senior researchers moved into university faculty positions. Despite these challenges, I remained committed to my work, independently pushing forward my research while continuously refining my expertise.
🔹 Resilience & Research – Despite these challenges, I successfully contributed to 15 national research projects, developing AI-driven solutions for medical imaging and successfully applied AI to real-world medical imaging problems, improving diagnostic accuracy and clinical workflows. My latest research paper is currently under review, marking another milestone in my journey.

As I stand at the intersection of AI, healthcare, and innovation, I am ready to take on new challenges that push the boundaries of technology

If you're here, you’re probably curious too. Let’s connect.
🔹 www.linkedin.com/in/csyurina 🔹