Young-Eun Lee

Introduction

Young-Eun Lee

• PhD (Feb. 2024, integrated MS and PhD Program)
• Dept. Brain and Cognitive Engineering at Korea University
• Lab: Pattern Recognition & Machine Learning Lab Homepage

Email: ye_lee@korea.ac.kr

Google Scholar

GitHub

Selected Paper

• Y.-E. Lee, S.-H. Lee, S.-H Kim, and S.-W. Lee, “Towards Voice Reconstruction from EEG during Imagined Speech,” AAAI Conference on Artificial Intelligence (AAAI), 2023.
• Y.-E. Lee, N.-S. Kwak, S.-W. Lee, “A Real-time movement artifact removal method for ambulatory brain-computer interfaces,” IEEE Trans. on Neural Systems & Rehabilitation Engineering, Vol. 28, No.12, 2020, pp. 2660-2670.
• Y.-E. Lee, H. M. Husin, M.-P. Forte, S.-W. Lee, and K. J. Kuchenbecker, “Learning to Estimate Palpation Forces in Robotic Surgery from Visual-Inertial Data,” IEEE Transactions on Medical Robotics and Bionics, Vol. 5, No. 3, 2023, pp. 496-506.
• M.-H. Lee, O.-Y. Kwon, Y.-J. Kim, H.-K. Kim, Y.-E. Lee, J. Williamson, S. Fazli, and S.-W. Lee, “EEG Dataset and OpenBMI Toolbox for Three BCI Paradigms: An Investigation into BCI Illiteracy,” GigaScience, Vol. 8, No. 5, 2019, pp. 1-16.

Publication

International Journals

• Y.-E. Lee, H. M. Husin, M.-P. Forte, S.-W. Lee, and K. J. Kuchenbecker, “Learning to Estimate Palpation Forces in Robotic Surgery from Visual-Inertial Data,” IEEE Transactions on Medical Robotics and Bionics, Vol. 5, No. 3, 2023, pp. 496-506.
• J.-H. Jeong, J.-H. Cho, Y.-E. Lee, S.-H. Lee, G.-H. Shin, Y.-S. Kweon, J. R. Millán, K.-R. Müller, and S.-W. Lee, “2020 International Brain-Computer Interface Competition: A Review,” Frontiers in Human Neuroscience, Vol. 16, 2022, pp. 898300.
• Y.-E. Lee, G.-H. Shin, M. Lee, and S.-W. Lee, “Mobile BCI dataset of scalp- and ear-EEGs with ERP and SSVEP paradigms while standing, walking, and running,” Scientific Data, Vol. 8, No. 315, 2021.
• Y.-E. Lee, N.-S. Kwak, S.-W. Lee, “A Real-time movement artifact removal method for ambulatory brain-computer interfaces,” IEEE Trans. on Neural Systems & Rehabilitation Engineering, Vol. 28, No.12, 2020, pp. 2660-2670.
• M.-H. Lee, O.-Y. Kwon, Y.-J. Kim, H.-K. Kim, Y.-E. Lee, J. Williamson, S. Fazli, and S.-W. Lee, “EEG Dataset and OpenBMI Toolbox for Three BCI Paradigms: An Investigation into BCI Illiteracy,” GigaScience, Vol. 8, No. 5, 2019, pp. 1-16.
• M.-H. Lee, J. Williamson, Y.-E. Lee, and S.-W. Lee, “Mental Fatigue in Central and Peripheral Field SSVEP and Its Effects on ERP Responses,” NeuroReport, Vol. 29, 2018, pp. 1301-1308.
• J.-H. Jeong, J.-H. Cho, K.-H. Shim, Y.-E. Lee, and S.-W. Lee, “NeuroBoT: Short-Term Brain-Machine Learning of Real-Time EEG Decoding for BMI-of-Things,” IEEE Transactions on Systems Man and Cybernetics: Systems. (Under review)

International Conferences

• S. Kim, Y.-E. Lee, S.-H. Lee, and S.-W. Lee, “Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEG,” Proc. of Interspeech, 2023.
• J. Lee, S.-H. Lee, Y.-E. Lee, S. Kim, S.-W. Lee, “Sentence Reconstruction Leveraging Contextual Meaning from Speech-Related Brain Signals,” 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2023.
• Y.-E. Lee, S.-H. Lee, S. Kim, S.-H. Kim, J.-S. Lee, and S.-W. Lee, “Speech Synthesis from Brain Signals Based on Generative Model,” Proc. 11th IEEE International Winter Conference on Brain-Computer Interface, Feb. 20-22, 2023.
• S. Kim, J.-W. Lee, Y.-E. Lee, S.-H. Lee, “Subject-Independent Classification of Brain Signals using Skip Connections,” Proc. 11th IEEE International Winter Conference on Brain-Computer Interface, Feb. 20-22, 2023.
• S.-H. Lee, Y.-E. Lee, S. Kim, S.-W. Lee, “Towards Neural Decoding of Imagined Speech based on Spoken Speech,” Proc. 11th IEEE International Winter Conference on Brain-Computer Interface, Feb. 20-22, 2023.
• Y.-E. Lee, S.-H. Lee, S.-H Kim, and S.-W. Lee, “Towards Voice Reconstruction from EEG during Imagined Speech,” AAAI Conference on Artificial Intelligence (AAAI), 2023.
• Y.-E. Lee and S.-H. Lee, “EEG-Transformer: Self-attention from Transformer Architecture for Decoding EEG of Imagined Speech,” Proc. 10th IEEE International Winter Conference on Brain-Computer Interface, Feb. 21-23, 2022.
• S.-H. Lee, Y.-E. Lee and S.-W. Lee, “Toward Imagined Speech based Smart Communication System: Potential Applications on Metaverse Conditions,” Proc. 10th IEEE International Winter Conference on Brain-Computer Interface, Feb. 21-23, 2022.
• Y.-E. Lee and S.-W. Lee, “Decoding event-related potential from ear-EEG signals based on ensemble convolutional neural networks in ambulatory environment,” Proc. 9th IEEE International Winter Conference on Brain-Computer Interface, Feb. 22-24, 2021.
• S.-H. Lee*, Y.-E. Lee*, S.-W. Lee, “Voice of your brain: Cognitive representations of imagined speech, overt speech, and speech perception based on EEG,” Arxiv preprint, 2021.
• Y.-E. Lee and M. Lee, “Decoding visual responses based on deep neural networks with ear-EEG signals,” Proc. 8th IEEE International Winter Conference on Brain-Computer Interface, Feb. 26-28, 2020.
• Y.-E. Lee, M. Lee, S.-W. Lee, “Reconstructing ERP signals using generative adversarial networks for mobile brain-machine interface,” Arxiv preprint, 2020.
• Y.-E. Lee, H. M. Husin, M. P. Forte, S.-W. Lee, K. J. Kuchenbecker, “Vision-based Force Estimation for a da Vinci Instrument Using Deep Neural Networks,” SAGES, 2020.

Domestic Conferences

• S. Kim, Y.-E. Lee, S.-H. Lee, S.-W. Lee, “Speech EEG classification based on residual learning for user-independent brain-computer interfaces,” Winter Symposium of the Korean Society of Brain Engineering, 2023.

Patents

• “Method and Apparatus for Speech Synthesis Based on Brain Signals During Imagined Speech,” Application Number: US 18/199,670 (U.S.A).
• “User Authentication Apparatus and Method Using Brainwave Signal According to Imagined Speech,” Application Number: US 17/884,870 (U.S.A).
• “Apparatus and Method for Left- and Right-Foot Classification Based on Brain Signals,” Registration Number: 10-2276991 (Korea).
• “Method and apparatus for speech synthesis based on brain signals during imagined speech,” Application Number: 10-2022-0173551 (Korea).
• “Smart Home Control System and Apparatus based on Brain-Computer Interface Using Minimum Stimulus,” Application Number: 10-2022-0163784 (Korea).
• “A method for user intent recognition through similarity comparison by extracting features from imagined speech and overt speech in brain-computer interface,” Application Number: 10-2022-0163782 (Korea).
• “Brain-Computer Interface System for Supporting New Language Acquisition Using Brain Signals,” Application Number: 10-2022-0173553 (Korea).
• “Bio-signal-based metaverse system implementation method for predicting and reconstructing user’s facial emotions and mouth shapes based on bio-signals,” Application Number: 10-2022-0163781 (Korea).
• “Personal authentication apparatus and system based on brain signals of imagined speech,” Application Number: 10-2021-0079992 (Korea).
• “Apparatus and method for left- and right-foot classification based on brain signals,” Application Number: 10-2018-0135194 (Korea).

Career

• Visiting Researcher at Max-Planck Institute (MPI) for Intelligent Systems, 2019.08.01 - 2020.01.31.
• Intern at IBM Korea Watson, 2016.07.01 - 2016.09.30.

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