Congratulations!!! Seongwoo’s paper, “Continuous Riemannian Geometric Learning for Sleep Staging Classification,” is accepted for presentation in BCI 2022.
Author: milab
[Jaeun’s MS Thesis Defense]
Congratulations!!! Jaeun made a successful defense for her MS thesis. She will graduate this coming February.
Wonsik, Wonjun, and Jee-Seok were awarded the “NAVER PhD Fellowship”.
Congratulation!! Wonsik, Wonjun, and Jee-Seok won the 2021 NAVER PhD Fellowship award. The fellowship is awarded to graduate students with top-quality research output.
[KHBM Award] Outstanding Trainee Award
Congratulations!!! Wonjun received the “Outstanding Trainee Award” in the 2021 KHBM Fall Workshop.
[KU 연구장려장학금] 전은진, 윤지석 수상
전은진, 윤지석 연구원이 고려대 정보대학이 우수 논문 제출한 수료연구생에게 수여하는 “KU 연구장려장학금”을 수상하였습니다.“연구장려장학금”은 고려대 정보대학이 연구력 향상을 위해 우수한 논문을 제출한 수료연구생에게 우수논문상과 더불어 연구장려장학금을 지급합니다. 축하합니다!
Accepted to ICDM 2021
Congratulations!!! Wonjun’s paper, “ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding” is accepted for presentation in ICDM 2021. W. Ko, W. Jung, E. Jeon, A. W. Mulyadi, and H.-I. Suk, “ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding,” Proc. 21st IEEE International Conference on Data Mining (ICDM), 2021. (Acceptance rate=20%)
Accepted to ACPR 2021
Congratulations!!! Wonjun’s paper, “Spectro-Spatio-Temporal EEG Representation Learning for Imagined Speech Recognition,” is accepted for presentation in ACPR 2021. W. Ko, E. Jeon, and H.-I. Suk, “Spectro-Spatio-Temporal EEG Representation Learning for Imagined Speech Recognition,” Proc. The 6th Asian Conference on Pattern Recognition (ACPR), 2021.
[PhD/MS Thesis Defences]
Congratulations! Eunji (Ph.D. program), and Yurim and Jaein (M.S. program) have successfully defended their thesis. They will acquire, respectively, doctoral and master’s degrees in August of this year.
Accepted to IEEE-TNNLS
Congratulations!!! Eunjin’s paper, “Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCI” is accepted for publication in IEEE-TNNLS.