I am an undergraduate student in the Computer Science and Engineering, and I am studying Medical AI as an joint major in JBNU. As an undergraduate researcher in the Medical AI lab, I am conducting research and projects in the field of Medical AI. I try to fill my life with things I love to do and constantly push myself to do what I want to do. I want to become an expert in the field of medical artificial intelligence, especially in the field of neural networks.
I’m interested in medical science, biomedical engineering, and the brain in general.
I think about how we can apply the intuition that happens in the human brain to AI models.
In AI, I am interested in Medical AI, especially in the field of neuroscience, where I would like to apply AI technology to uncover the secrets of the brain. I am majoring in Medical AI and working as an undergraduate research student in a related lab.
I’m interested in analyzing and modeling data from multiple disciplines.
I’m currently working on the Litmus Renewal Project maintenance and development of the Reader test webpage.
I’ve been working on the algorithm.
I value experience. I’m interested in many things, so I’ve had many different experiences, including being an exchange student and vice president of a club.
I love the physicality of books. Reading is more of a routine than a hobby for me.
I love to travel. I’d like to visit the Bermuda Triangle, the Serengeti, and other mysterious places, as well as milky way.
I am currently working on my major project ‘Creating an intelligent online labeling tool for building AI training datasets’ in the class of 2024, Industry-Academic Capstone 3. As the team leader, I am in charge of FE, BE development and AI.
As ALPS Vice Chairman in 2024, he conducted LITMUS RENEWAL PROGRAM ‘https://litmus.jbnu.ac.kr/' ‘, an online budget program, for six months from March to August, and was mainly responsible for FE work.
I researched and developed a segmentation model for MRI image-based cancer diagnosis automation with the ‘LGG Segmentation Dataset’ during January-February 2024. Medical image segmentation using this dataset. I conducted research on the latest segmentation model, change of existing model, and performance comparison.