가톨릭대학교가톨릭대학교인공지능학과

 

교수진

홈

겸무교원

안내사항

  • 교수진 정렬 기준 : 학과명, 직위, 입사일, 이름 순서임.
이민지(Lee Minji ) 프로필 이미지 학과장

이민지 조교수

Lee Minji

연구분야

뇌공학, 생체신호처리, 의료 인공지능

연구키워드

뇌-컴퓨터 인터페이스 멀티모달 학습 설명가능 인공지능 생체신호처리

교수소개


						
이민지 교수는 뇌파, 심전도 등 생체신호와 임상데이터를 활용한 의료 인공지능을 연구하고 있다. 주요 연구 주제는 생체신호 기반 질환 및 상태 예측, 멀티모달 학습, 뇌-컴퓨터 인터페이스이며, 해석 가능한 머신러닝·딥러닝 모델 개발에 관심을 두고 있다. 2021년 고려대학교에서 해석 가능한 딥러닝을 활용한 의식 변화 상태의 각성 및 자각 수준 정량화 연구로 박사학위를 받았으며, 이후 SK하이닉스에서 Data Scientist로 근무하였다. 2023년부터 가톨릭대학교에서 계산신경지능 연구실을 운영하고 있으며, 미국, 독일, 벨기에 등과 국제공동연구를 수행하고 있다.
Professor Minji Lee studies medical AI using biosignals such as EEG and ECG, as well as clinical data. Her research focuses on biosignal-based prediction of diseases and physiological states, multimodal learning, and brain-computer interfaces. She is interested in developing interpretable machine learning and deep learning models. She received her Ph.D. from Korea University in 2021 for research on quantifying arousal and awareness in altered states of consciousness using interpretable deep learning. She subsequently worked as a Data Scientist at SK hynix. Since 2023, she has led the Computational Neural Intelligence Lab at The Catholic University of Korea. She conducts international collaborative research with researchers in the United States, Germany, and Belgium.

최종학력

2021.02.25 | 고려대학교 | 뇌공학과 | 공학박사

연구실적

  • 2026.08 | 교신저자 | EXPERT SYSTEMS WITH APPLICATIONS, 제323권
    CenterIR: An imbalance-aware deep regression framework for EEG-based depression severity estimation in older adults
  • 2026.07 | 교신저자 | NEUROIMAGE: CLINICAL, 제51권, pp.1-11
    Neuroimaging biomarkers of non-invasive brain stimulation in post-stroke recovery: EEG and fMRI perspectives
  • 2026.06 | 교신저자 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 제1권 1호, pp.1-15
    Cross-Subject Decoding of Finger-Level Motor Imagery in Stroke Patients Using Hierarchical Connectivity and Dempster–Shafer Fusion
  • 2025.12 | 공동저자 | EXPERT SYSTEMS WITH APPLICATIONS, 제294권
    Functional connectivity guided deep neural network for decoding high-level visual imagery
  • 2025.12 | 교신저자 | SCIENTIFIC REPORTS, 제15권 1호
    Resting-state EEG dual biomarker for motor-cognitive function in elderly individuals
  • 2025.10 | 공동저자 | IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, 제55권 10호, pp.6569-6584
    Local-Global Temporal Fusion Network With an Attention Mechanism for Multiple and Multiclass Arrhythmia Classification
  • 2025.08 | 교신저자 | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 제33권, pp.3000-3013
    DualDyConvNet: Dual-Stream Dynamic Convolution Network via Parameter-Efficient Fine-Tuning for Predicting Motor Prognosis in Subacute Stroke
  • 2025.08 | 공동저자 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 제74권
    Asynchronous Quadrature-Phase Undersampling Technique for Wide-Frequency Impedance Measurement
  • 2025.05 | 공동저자 | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 제33권, pp.1907-1917
    Quantifying Sleep Quality Through Delta-Beta Coupling Across Sleep and Wakefulness
  • 2025.04 | 교신저자 | EXPERT SYSTEMS WITH APPLICATIONS, 제270권
    A brain-inspired model for multi-step forecasting of malignant arrhythmias
  • 2025.03 | 제1저자 | BRAIN CONNECTIVITY, 제15권 2호, pp.57-58
    Charting the Frontiers of Brain Connectivity: From Rehabilitation to Imagination
  • 2025.03 | 공동저자 | EXPERT SYSTEMS WITH APPLICATIONS, 제266권
    Multi-layer prototype learning with Dirichlet mixup for open-set EEG recognition
  • 2025.01 | 공동저자 | ISCIENCE, 제28권 1호
    A pilot human study using ketamine to treat disorders of consciousness
  • 2024.12 | 제1저자 | CURRENT OPINION IN NEUROLOGY, 제37권 6호, pp.614-620
    Artificial intelligence and machine learning in disorders of consciousness
  • 2024.11 | 제1저자 | APPLIED SCIENCES-BASEL, 제14권 21호
    Neuromodulation Effect According to Lesion Location After Dual-Mode Brain Stimulation in Patients with Subacute Stroke: A Preliminary Study
  • 2024.09 | 교신저자 | JOURNAL OF MEDICAL INTERNET RESEARCH, 제26권
    Early Prediction of Cardiac Arrest in the Intensive Care Unit UsingExplainable Machine Learning:Retrospective Study
  • 2024.07 | 공동저자 | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 제32권, pp.2793-2804
    Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control
  • 2024.06 | 제1저자 | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 제32권, pp.2533-2544
    Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network
  • 2024.04 | 제1저자 | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 제32권, pp.1767-1778
    Multi-Task Heterogeneous Ensemble Learning-Based Cross-Subject EEG Classification Under Stroke Patients
  • 2023.12 | 교신저자 | JOURNAL OF MEDICAL INTERNET RESEARCH, 제25권
    Explainable Artificial Intelligence Warning Model Using an Ensemble Approach for In-Hospital Cardiac Arrest Prediction: Retrospective Cohort Study
  • 2023.08 | 제1저자 | FRONTIERS IN PHYSIOLOGY, 제14권
    SeriesSleepNet: an EEG time series model with partial data augmentation for automatic sleep stage scoring
  • 2022.02 | 제1저자 | NATURE COMMUNICATIONS, 제13권 1호, pp.1-14
    Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning
  • 2026.01.06 | 주발명자 | 일동바이오사이언스(주)
    ‘장-뇌 축 기반 수면 개선 예측 및 유산균 추천 장치 및 방법’의 기술이전
  • 2023.12.20 | 주발명자 | (주)씨어스테크놀로지
    '다채널 생체신호 기반 자동 수면 단계 분류 장치 및 방법'의 기술이전