Congratulations!!! Wonsik and Jaeun received an “Excellent Poster Award” at KHBM 2020.
Welcome to the Machine Intelligence Lab
The Machine Intelligence Lab (MILAB) at Korea University is directed by Professor Heung-Il Suk.
We are tackling fundamentally open problems in developing biologically plausible machine/deep learning algorithms for various applications including medical/computer vision, brain-computer interfaces, healthcare, and neuroinformatics.
Research Areas
Machine/Deep Learning
Developing novel deep learning methods that can integrate multiple neuroimaging modalities
AI in Neuroinformatics
Developing machine-learning algorithms that can estimate the underlying functional patterns from fMRI images and utilize the estimated information for disease diagnosis/prognosis
AI in Medical/Computer Vision
Developing various applications for medical/computer vision tasks, where the objective is to achieve state-of-the-art performance with human-level interpretability in mind
AI in Brain-Computer Interface
Developing BCI-oriented but paradigm-independent algorithms that intelligently remove artifacts/noise and learn a user-specific brain signal patterns by utilizing their resting-state signals
AI in Healthcare
Developing deep architectures for disease phenotying, future patients’ state prediction, missing value imputation, and uncertainty quantification from Electronic Health Records (EHR) for better understanding and investigation of the underpinning phenomena in healthcare observations
Lab’s latest news
6 Papers Accepted to CKAIA 2020
Congratulations!!! 6 papers have been accepted to CKAIA 2020.
Accepted to IEEE-TNNLS
Congratulations!!! Eunji’s paper, “Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction,” is accepted for publication in IEEE-TNNLS.
Accepted to HBM
Congratulations!!! Eunji’s paper, titled “Identifying Resting-State Effective Connectivity Abnormalities in Drug-Naïve Major Depressive Disorder Diagnosis via Graph Convolutional Networks”, is...