Building AI-enabled Computational Models for Brain Science and Engineering
Our ultimate goal is to build AI-enabled models and develop their applications in real-world scenarios using brain signals.
To this end, our main research themes include the investigation of brain functions measured by various neuroimaging modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), biosignals, and a variety of information and data using AI models along with signal processing and machine learning techniques. We believe our findings will be gainfully applied to develop essential applications in various domains.
How can we build such AI-enabled models for brain signals and apply the models in real-world scenarios?
What would be the most feasible applications for us to focus on?
If you want to join BSPL, please send your bio/personal statement and/or CV to PI.
BSPL 연구실에서는 이러한 연구들에 관심있는 석사, 석-박통합, 박사과정 학생 및 연구원을 모집하고 있습니다. 관심있는 분은 간단한 자기소개와 CV 등을 이메일로 보내주시고, 추가적으로 궁금한 사항을 문의하기 위한 면담을 요청해 주시기 바랍니다.
Minseok Choi, Hyun-Chul Kim, Inchan Youn, Song Joo Lee, Jong-Hwan Lee
Juhyeon Lee; Jong-Hwan Lee
Jundong Hwang; Niv Lustig; Minyoung Jung; Jong-Hwan Lee
[PubMed / Google Scholar / Journal Home]
Yeji Kim; Juhyeon Lee; Marion Tegethoff; Gunther Meinlschmidt; Seung-Schik Yoo; Jong-Hwan Lee
Main manuscript, Table, Supplementary materials
[PubMed / Google Scholar / Journal Home]
Jinwoo Hong; Jundong Hwang; Jong-Hwan Lee
[PubMed / Google Scholar / Journal Home]