From Medicine to AI: Bridging Science and Technology

Ph.D. Candidate | Medical AI Researcher
Computer Vision • Medical Imaging • Generative AI • Multimodal Learning

From Medicine to AI: Bridging Science and Technology

What if AI could bridge the gap between medicine and real-world clinical impact?
This question has shaped my journey across disciplines, leading me to contribute to 15 national-level research projects in medical AI.

I grew up in both South Korea and the United States, gaining a global perspective across two education systems. My academic journey began in biomedical science and evolved into AI, driven by a strong interest in data-driven problem solving.

🔹 University of Minnesota Twin Cities (B.S. in Biology)
Conducted leukemia research at a university hospital, focusing on Natural Killer cells.
Undergraduate thesis on stem cell therapy for pediatric leukemia.

🔹 Transition from Biology to AI
Started coding while analyzing biological data, progressively transitioning into AI-driven research that integrates domain expertise with computational methods.

🔹 Medical AI Researcher (Government-Funded Research Institute)
Worked as a full-time researcher while pursuing a PhD, contributing to 15 national research projects.
Gained hands-on experience with real-world clinical data, large-scale systems, and cross-disciplinary collaboration across hospitals, engineers, and industry partners.

🔹 Applied Research & Technical Strength
Developed AI solutions for medical imaging with a focus on robustness, scalability, and real clinical applicability.
Experienced in building end-to-end pipelines for medical image analysis, including model development, evaluation, and deployment-oriented design.

🔹 Current Work (Ph.D. Candidate)
My latest research is currently under peer review.
I am actively expanding my portfolio with projects that bridge research innovation and real-world clinical applications.

Research Focus

• Medical Image Analysis (CT, MR, Multimodal)

• Generative AI & Representation Learning

• Clinical AI Systems for Real-World Deployment

• Multimodal Biomedical AI (Imaging, RNA-seq, iPSC-based Data) 

As an AI researcher with both biomedical and technical expertise, I bring a unique perspective that connects clinical understanding with machine learning implementation.

I am particularly interested in building scalable AI systems that translate into real-world healthcare impact.

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