Publication
CGM-EEG: Cross-Gated Mamba for Spatio-Temporal Eeg Representation Learning
Apr 8, 2026 · 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)
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Public profile
Emil Kim
@emeelkaa
AI Researcher | Biomedical Signals, Medical Imaging & Healthcare AI
Hello! My name is Emil. I am currently a second-year M.S. candidate in the IC&ML Lab, Graduate School of AI, Pusan National University.
Busan, Korea, SouthPusan National University
Featured
A few things that best show this member's work and contribution.
About
Before starting my graduate studies, I obtained my B.S. in Computer Science and Engineering at Pusan National University. I spend most of my time exploring biosignals, multimodal representation learning, and medical image analysis — usually with too many tabs open and a GPU running somewhere.
Career
Experience, skills, projects, and achievements.
AI Researcher | Biomedical Signals, Medical Imaging & Healthcare AI
Experience
Graduate Researcher
Image Computing and Machine Learning Laboratory
Sep 2024 — PresentAs 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. Using Python and PyTorch, I developed my research findings into academic publications and conference presentations.
Education
MSc Artificial Intelligence
Pusan National University
2025 — 2027Conducted research in EEG representation learning, biomedical signal analysis, and multimodal medical imaging. 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 will be presented at MICCAI 2026 in Strasbourg.
BSc Computer Science
Pusan National University
2020 — 2025Studied computer vision, machine learning, data mining, and AI programming, with a focus on applying AI to real-world problems. For my bachelor’s thesis, I developed an AI model for medical image analysis for Parkinson’s disease diagnosis.
Research and publications
A compact preview of this member's public research layer.
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