About

Welcome! I am Kyungjin Kim (but feel free to call me James 🙂), a Ph.D. student at Seoul National University (SNU). My research focuses on AI-driven biomedical data analysis and system design. I am always open to exciting collaborations and look forward to connecting with researchers and professionals in related fields.

Research Interest

I am deeply interested in the expansive field of digital health, particularly in applying advanced computational methods and biomedical engineering to drive innovation in healthcare. My research focuses on the following areas:

AI and XAI-Driven Biomedical Data Analysis

I collaborate with medical professionals to apply statistical methods, machine learning, and explainable AI (XAI) in biomedical data analysis. My goal is to translate data-driven insights into actionable knowledge for healthcare applications, enhancing decision-making and patient outcomes.

AI Engineering for Domain-Optimized Medical Intelligence

My research focuses on developing AI models tailored for medical applications, addressing the unique challenges of the healthcare domain. This includes designing robust architectures, integrating multimodal data sources, and ensuring interpretability and reliability in clinical decision support. I work with diverse medical data types, including radiological images, electronic health records, and structured and unstructured clinical information, aiming to advance AI-driven diagnostics and healthcare automation.

Interactive Visualization and Human-Centered AI

I design and develop interactive visualization tools and user interfaces to facilitate seamless exploration and interpretation of medical data. My research centers on Human-Centered AI, bridging the gap between artificial intelligence and real-world applications. By integrating intuitive design principles with AI, I strive to create interactive systems that enhance usability, interpretability, and accessibility in medical and biomedical domains.

Neural Recording and Prosthesis

While my primary focus is on AI-driven research, I am also interested in biomedical instrumentation, particularly in MEMS-based fabrication for electrical stimulation and medical sensor development. I aim to further explore these areas to bridge AI with real-world biomedical applications, contributing to advancements in neural interfaces and assistive prosthetic technologies.