Minho Lee

Emailminho.leenu.edukz

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1 Similar Profiles

1 Finished
4 Active

A realistic assistant for patients with paralysis based on a multimodal and explainable Brain-Computer Interface, developed using zero-calibration, paradigm-independence and stimulus minimization technologies
Lee, M. (PI)
4/1/25 → 12/31/27
Project: Government
Transforming Epilepsy Care in Kazakhstan with Machine Learning-Driven Brain-Computer Interfaces
Abibullaev, B. (PI), Utebekov, Z. (Co-PI), Lee, M. (Other Faculty/Researcher), Akhmedullin, R. (Other Faculty/Researcher) & Zollanvari, A. (Other Faculty/Researcher)
2/4/25 → 12/31/27
Project: FDCRGP
Zero-calibration, Paradigm-independent, and Explainable Brain-Computer Interfacing: Realistic Assistant for Palsy Patient
Lee, M. (PI)
1/1/23 → …
Project: International
Building Capacity to Improve Air Quality in South Asia: Reducing PM2.5 Through Low-Cost Sensor Network Driven Policy Decisions
Lee, M. (PI)
1/1/22 → 12/31/25
Project: International
Interpretable artificial intelligence for detection of psychiatric disorders based on multi-modal neuroimaging data
Lee, M. (PI), Fazli, S. (Co-PI) & Viderman, D. (Co-PI)
1/1/20 → 12/31/22
Project: FDCRGP

40 Conference contribution
19 Article
2 Chapter
2 Paper
More

Benchmarking Federated Few-shot Learning for Video-based Action Recognition
Tu, N. A., Aikyn, N., Makhanov, N., Abu, A., Wong, K. S. & Lee, M. H., 2024, (Accepted/In press) In: IEEE Access. 3519254.
Research output: Contribution to journal › Article › peer-review

Open Access
EAV: EEG-Audio-Video Dataset for Emotion Recognition in Conversational Contexts
Lee, M. H., Shomanov, A., Begim, B., Kabidenova, Z., Nyssanbay, A., Yazici, A. & Lee, S. W., Dec 2024, In: Scientific Data. 11, 1, 1026.
Research output: Contribution to journal › Article › peer-review

Open Access
3 Citations (Scopus)
FedFSLAR: A Federated Learning Framework for Few-shot Action Recognition
Tu, N. A., Abu, A., Aikyn, N., Makhanov, N., Lee, M. H., Le-Huy, K. & Wong, K. S., 2024, Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2024. Institute of Electrical and Electronics Engineers Inc., p. 270-279 10 p. (Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2024).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
8 Citations (Scopus)
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Bernárdez, G., Telyatnikov, L., Montagna, M., Baccini, F., Papillon, M., Ferriol-Galmés, M., Hajij, M., Papamarkou, T., Bucarelli, M. S., Zaghen, O., Mathe, J., Myers, A., Mahan, S., Lillemark, H., Vadgama, S., Bekkers, E., Doster, T., Emerson, T., Kvinge, H. & Agate, K. & 53 others, Ahmed, N. K., Bai, P., Banf, M., Battiloro, C., Beketov, M., Bogdan, P., Carrasco, M., Cavallo, A., Choi, Y. Y., Dasoulas, G., Elphick, M., Escalona, G., Filipiak, D., Fritze, H., Gebhart, T., Gil-Sorribes, M., Goomanee, S., Guallar, V., Imasheva, L., Irimia, A., Jin, H., Johnson, G., Kanakaris, N., Koloski, B., Kovač, V., Lecha, M., Lee, M., Leroy, P., Long, T., Magai, G., Martinez, A., Masden, M., Mežnar, S., Miquel-Oliver, B., Molina, A., Nikitin, A., Nurisso, M., Piekenbrock, M., Qin, Y., Rygiel, P., Salatiello, A., Schattauer, M., Snopov, P., Suk, J., Sánchez, V., Tec, M., Vaccarino, F., Verhellen, J., Wantiez, F., Weers, A., Zajec, P., Škrlj, B. & Miolane, N., 2024, In: Proceedings of Machine Learning Research. 251, p. 420-428 9 p.
Research output: Contribution to journal › Conference article › peer-review
Multi-Document Question Answering with Lightweight Embeddings-based Document Reranker
Aitymbetov, N., Lee, M. H. & Tu, N. A., 2024, Proceedings - 2024 International Conference on Advanced Technologies for Communications, ATC 2024. Bao, V. N. Q. & Anh, D. T. (eds.). IEEE Computer Society, p. 707-712 6 p. (International Conference on Advanced Technologies for Communications).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Minho Lee, PhD

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Collaborations and top research areas from the last five years

Dive into details

A realistic assistant for patients with paralysis based on a multimodal and explainable Brain-Computer Interface, developed using zero-calibration, paradigm-independence and stimulus minimization technologies

Transforming Epilepsy Care in Kazakhstan with Machine Learning-Driven Brain-Computer Interfaces

Zero-calibration, Paradigm-independent, and Explainable Brain-Computer Interfacing: Realistic Assistant for Palsy Patient

Building Capacity to Improve Air Quality in South Asia: Reducing PM2.5 Through Low-Cost Sensor Network Driven Policy Decisions

Interpretable artificial intelligence for detection of psychiatric disorders based on multi-modal neuroimaging data

Benchmarking Federated Few-shot Learning for Video-based Action Recognition

EAV: EEG-Audio-Video Dataset for Emotion Recognition in Conversational Contexts

FedFSLAR: A Federated Learning Framework for Few-shot Action Recognition

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain

Multi-Document Question Answering with Lightweight Embeddings-based Document Reranker

Minho Lee, PhD

Fingerprint

Collaborations and top research areas from the last five years

Projects

Research output