Congratulations!!! Two papers by Jaein and Wonsik are accepted for presentation in MICCAI, 2021.
Congratulation!! A paper on leveraging population-based and personalized reference Intervals for liver and spleen volumes in healthy individuals and those with viral hepatitis has been accepted for publication in Radiology. D.W. Kim, J. Ha, S. Lee, J.H. Kwon, N.Y. Kim, Y. Sung, J.-S. Yoon, H.-I. Suk, Y. Lee, and B.-K. Kang, “Population-based and Personalized Reference Intervals...
Congratulations!!! Wisnu’s work of “ProtoBrainMaps: Prototypical Brain Maps for Alzheimer’s Disease Progression Modeling” is accepted for presentation in MIDL.
Congratulation!! Our co-work with Prof. Min on “Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex” is accepted for publication in NeuroImage. B.-K. Min*, H. S. Kim, W. Ko, M.-H. Ahn, H.-I. Suk, D. Pantazis, R. T. Knight, “Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex,” NeuroImage, Accepted. (* Corresponding author)
Congratulations!!! Wonjun and Eunjin’s review paper, “A Survey on Deep Learning-based Short/Zero-calibration Approaches for EEG-based Brain-Computer Interfaces,” has been accepted for publication in Frontiers in Human Neuroscience (JCR-IF: 2.673).
Congratulations!!! Wonsik’s work on “Deep Recurrent Model for Individualized Prediction of Alzheimer’s Disease Progression” is accepted for publication in NeuroImage.
Congratulations!!! Jiyeon and Wonjun’s paper, titled “A Unified Framework for Personalized Regions Selection and Functional Relation Modeling for Early MCI Identification,” is accepted for publication in NeuroImage.
Functional MRI – and Machine/Deep-Learning-based Brain Disorder/Disease Diagnosis and Prognosis We seek a couple of highly motivated graduate students on functional brain imaging analysis and machine/deep learning-based brain disease diagnosis and prognosis. It is especially encouraged for those eager to develop advanced brain network modeling and functional MRI-based diagnostic methods by developing or applying recent...
고원준, 전은지 연구원이 고려대 최우수대학원생에게 수여하는 “KU Graduate Student Achievement Award”를 수상하였습니다.“KU Graduate Student Achievement Award” 는 본교 대학원생의 학문적, 사회적 업적을 발굴, 격려함으로써 성취의욕을 고취하고 우수성을 대외적으로 홍보하고자 고려대 전체 대학원생 중에서 30여명을 선발합니다. 축하합니다!
Congratulations!!! Wonjun’s work on “Multi-Scale Neural Network for EEG Representation Learning in BCI” is accepted to IEEE Computational Intelligence Magazine (IF: 9.083).