I am a Ph.D candidate in Artificial Intelligence at Korea University.
- Medical/Computer Vision
- Generalizable/Foundational Modeling, Explainable AI (XAI), Representation Learning, and Biomedical image analysis
- Programming Language: Python, Visual C/C++, Javascript, R, and MATLAB
- Deep Learning Framework: TensorFlow/Keras, PyTorch
-
Multi-Scale Minimal Sufficient Representation Learning for Domain Generalization in Sleep Staging, Under Review
-
Integrating Multimodal Large Language Models with Adaptive Context-Aware Decoding for Robust Medical Image Segmentation, Under Review
-
DyMix: Dynamic Frequency Mixup Scheduler- based Unsupervised Domain Adaptation for Enhancing Alzheimer’s Disease Identification, Under Review
-
IdenBAT: Disentangled Representation Learning for Identity-Preserved Brain Age Transformation, Under Review
-
FIESTA: Fourier-based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation, Under Review
-
Transferring Ultra-high Field Feature Representations for Intensity-Guided Brain Segmentation of Low Field Magnetic Resonance Imaging, IEEE TNNLS
-
[2025] A Quantitatively Interpretable Model for Alzheimer’s Disease Prediction using Deep Counterfactuals, NeuroImage, JCR-IF: 4.7, Neuroimaging: 1/15
-
[2025] Linear Fusion-Based Dual-MR Contrast Enhancement for Improved Choroid Plexus Segmentation, ISMRM'25, Oral Presentation
-
[2024] Domain Generalization for Medical Image Analysis: A Review, Proceedings of the IEEE, JCR-IF: 23.2, Engineering, Electrical & Electronic 2/353
-
[2024] Frequency Mixup Manipulation based Unsupervised Domain Adaptation for Brain Disease Identification, ACPR'24, Oral Presentation
-
[2023] Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer’s Disease Diagnosis Model, IEEE TPAMI, JCR-IF: 24.314, Computer Science & Artificial Intelligence: 2/144
-
[2023] Age-Aware Guidance via Masking-Based Attention in Face Aging, CIKM'23, 27.4% acceptance rate
-
[2023] Estimating Explainable Alzheimer’s Disease Likelihood Map via Clinically-Guided Prototype Learning, NeuroImage, JCR-IF: 7.4, Neuroimaging: 2/14
-
[2022] Quantifying Explainability of Counterfactual-Guided MRI Feature for Alzheimer’s Disease Prediction, MedNeurIPS'22
-
[2022] Clinically-guided Prototype Learning and Its Use for Explanation in Alzheimer’s Disease Identification, MedNeurIPS'22
-
[2022] A Novel Knowledge Keeper Network for 7T-Free But 7T-Guided Brain Tissue Segmentation, MICCAI'22
-
[2020] VIGNet: A Deep Convolutional Neural Network for EEG-based Driver Vigilance Estimation, IEEE IWCBCI'20
-
Domestic Conferences (1 KHBM, 1 IEIE, 1 IPIU, 1 KSEE, 3 KAIA, 1 CKMS, 2 KCR)
- [US Patent Registration] METHOD AND APPARATUS FOR REASONING AND REINFORCING DECISION IN BRAIN DISEASE DIAGNOSIS MODEL (No. 17714390)
- [US Patent Application] BRAIN IMAGE-BASED QUANTITATIVE BRAIN DISEASE PREDICTION METHOD AND APPARATUS (No. 18212261)
- [KR Patent Registration] 알츠하이머병 진단 모델의 결정을 해석하고 강화하는 방법 및 장치 (No. 10-2593036)
- [KR Patent Registration] 분류 결과 설명이 가능한 반 사실적 맵 생성 방법 및 그 장치 (No. 10-2496769)
- [KR Patent Registration] 자기공명영상 기반 뇌질환 예측 방법 및 장치 (No. 10-2760232)
- [KR Patent Application] 뇌혈관계 다중 분할 기반의 뇌동맥류 검출 장치 (No. 10-2024-0169281)
- [KR Patent Application] 불확실성 지침을 활용한 푸리에 기반 의미론적 증강 장치 (No. 10-2024-0112696)
- [Technology Transfer/KR Patent Registration] 반려동물 관리시스템 및 방법 (No. 10-1983101)
- [Software Registration] 뇌 영상 기반 설명 가능한 알츠하이머병 조기 예측 프로그램 (No. No. 114471-0002565)
- [2024] TopCow2024 Grand Challenge, MICCAI - Detection (CTA&MRA): 2nd; Segmentation (CTA&MRA): 3rd; Classification (CTA&MRA): 4th
- [2023] KU Achievement Award 2022, Korea University - Awarded to the Best Student in Each Department
- [2023] 4th JW Foundation Fundamental Scientist Scholarship, JW Foundation
- [2023] NAVER Ph.D. Fellowship Award 2022, Naver Corp.
- [2022] Qualcomm Innovation Fellowship Korea 2022, Qualcomm AI Research
- [2022] KT Business Startup Idea Challenge, KT Enterprise - Excellence Award (2nd)
- [2022] Announcement of Outstanding Research Results at the Graduate School of Artificial Intelligence Symposium (Coex Grand Room), Artificial Intelligence Graduate School Council (AIGSC)
- [2022] DataHub Team BK Fellowship Scholarship, Korea University
- [2022] KU Graduate Student Achievement Scholarship, Korea University
- Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Medical Imaging (TMI), Neural Networks and Learning Systems (TNNLS), Artificial Intelligence Review, Neural Networks
- Conference: International Conference on Computer Vision and Pattern Recognition (CVPR), The AAAI Conference on Artificial Intelligence (AAAI), International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), International Conference on Medical Imaging with Deep Learning (MIDL)
- Tel: +82-2-3290-3738
- Lab: https://milab.korea.ac.kr
- E-mail: ksohh@korea.ac.kr