About

My experience includes designing neural network architectures, optimizing deep learning models, and multimodal learning, with a research focus on biosignals and medical image analysis.

Career

Experience, skills, projects, and achievements.

Experience: 3 years

ML Engineer & AI Researcher | Computer Vision and Signal Processing

Experience

Graduate Researcher Assistant

Image Computing and Machine Learning Laboratory

Sep 2024 — Dec 2026

As a researcher in the Image Computing and Machine Learning Laboratory, I conducted AI research based on medical imaging and biomedical signals. My responsibilities included EEG and fMRI data preprocessing, deep learning model design and implementation, and experimental evaluation and performance analysis.

Education

MSc Artificial Intelligence

Pusan National University

2025 — 2027

Conducted research in EEG representation learning and EEG to fMRI translation framework. Developed a spatio-temporal state-space model for EEG that improved decoding performance by 6.6% while reducing inference latency by 7.1%, presented as an oral paper at IEEE ISBI 2026 in London. For my master’s thesis, I developed a lightweight state-space architecture for EEG-to-fMRI translation, reducing model parameters by 3.2× and peak memory usage by 2.3%. The work was presented at MICCAI 2026 in Strasbourg.

BSc Computer Science

Pusan National University

2020 — 2025

Took courses on computer vision, machine learning, data mining, and AI programming. For thesis, I developed a deep learning model for medical image analysis for Parkinson’s disease diagnosis.

Research and publications

A compact preview of this member's public research layer.

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Research in biomedical AI, focusing on EEG representation learning, medical imaging, and multimodal EEG-to-fMRI translation using efficient deep learning architectures.

Biosignal AnalysisMultimodal Representation LearningFoundation ModelsMedical Image AnalysisEEG