PUBLICATIONS

Google Scholar Citation

https://scholar.google.com/citations?user=MXUabqcAAAAJ&hl=ko

* Corresponding author, † Co-first author

**Red highlight: Top-tier AI Conference

• "Hyper Neuro-adaptive Learning Enables A Fully EEG-guided Shared Autonomy System," 2025, Under review.

• “Artificial Intelligence in Veterinary Medicine for Companion Animals: A Comprehensive Survey,” 2025, Under Review.

• "Sleep Efficiency Prediction via Interpretable Learning Framework with Hyperparameter Optimization from Wearable Lifelog Data," 2025, Under Review.

• "E2T: EEG-to-Trajectory Transformer for Motor Imagery-based Fully-DoF Motion Prediction," 2025, Under Review.

• J.-H. Jeong†, M. Lee†, C. Lee, S.-H. Yu, H.-Y. Park, S.-N. Jang, R. D. Sanders, and S.-W. Lee, "EEG-based Cross-subject Prediction for Consciousness State Transitions under Sedation using a Deep Learning Framework," IEEE Journal of Biomedical and Health Informatics, 2025, Accepted.
  (2024-JCR-IF: 6.8, JIF Percentile TOP 4.5%)

• E. Lee, J. Jeong, G. Jo, T. Lee, G.-M. Moon, Y.-D. Seo, J.-H. Jeong*, "A self-adaptive framework for child healthcare in IoT environment using AI-based prediction," Pervasive and Mobile Computing, Vol. 116, 2026, p. 102153.
  (2024-JCR-IF: 3.5, JIF PERCENTILE TOP 37.5%)

• S.-N Jang, H.-Y. Park, S.-W. Kiim, H. Roh, A.-H. Kim, T.-H. Kam, and J.-H. Jeong*, "Neuro-SIT : Neural Speech Imagery Transformer with Token-Level Representation for Sentence-Level EEG Decoding," The 41th ACM/SIGAPP Symposium On Applied Computing (SAC '26**), Thessaloniki, Greece, Mar. 23-27, 2026.

• G. Jo, K. Jeong, H. Seo, J.-H. Jeong, and E. Lee, "Improving Interoperability in Object Detection across Diverse Datasets,“ The 41th ACM/SIGAPP Symposium On Applied Computing (SAC '26**), Thessaloniki, Greece, Mar. 23-27, 2026.

• S.-H. Yu†, H.-Y. Park†, E. Lee, T.-E. Kam, J.-H. Jeong*, "DeepSMR: Decoding High-Complex Motor Imagery via Subject-Dependent Multi-Feature Refinement in Deep Convolutional Networks," Computers in Biology and Medicine, Vol. 197, 2025, p. 110920.
  (2024-JCR-IF: 6.3, JIF Percentile Top 5.9%)

• J. Jeong†, J.-H. Jeong†, G.-M. Moon, Y.-D. Seo and E. Lee, "Application of Explainable Artificial Intelligence for personalized childhood weight management using IoT data," Computers in Biology and Medicine, Vol.196, 2025, pp. 110855.
  (2024-JCR-IF: 6.3, JIF Percentile Top 5.9%)

• K. Jeong, S. Park, G. Jo, H. Seo, N. Choi, S. Jang, G. Park, Y.-D. Seo, Y.-H. Brad. Kim, J.-H. Jeong, S.-H. Hyun, J. Choi, and E. Lee*, “SEPO-FI: Deep-Learning Based Software to Calculating Fusion Index of Muscle Cells,” Computers in Biology and Medicine, Vol.186, 2025, pp. 109706.  
  (2024-JCR-IF: 6.3, JIF Percentile Top 5.9%)

• D.-Y. Kim, D.-K. Han, J.-H. Jeong, S.-W. Lee*, "Calibration-Free Driver Drowsiness Classification with Prototype-Based Multi-Domain Mixup," IEEE Transactions on Intelligent Transportation Systems, 2025, Vol. 26, No. 3, pp. 2955-2966.
  (2024-JCR-IF: 8.4, JIF Percentile Top 2.7%)

• K. Jeong, H. Oh, H. Seo, G.Cho, J. Jeong, Y. Lee, H. Park, J. Choi, Y.-D. Seo, J.-H. Jeong*, E. Lee*, "IoT and AI Systems for Enhancing Bee Colony Strength in Precision Beekeeping: A Survey and Future Research Directions," IEEE Internet of Things Journal, Vol. 12, No. 1, 2025, pp. 362-389.
  (2024-JCR-IF: 8.9, JIF Percentile Top 4.2%)

• K. Jeong, G. Jo, J. Lee, Brad Kim, J. Choi, H. Oh, J.-H. Jeong, and E. Lee, "Artificial Intelligence in Meat Processing: A Comprehensive Review of Data-Driven Applications and Future Directions," Meat and Muscle Biology, Vol. 9, No. 1, 2025, pp.1-30. 

• H. Oh†, H. Oh†, J. Jeong, S. Kim, K. Jeong, S.-H. Hyun, J.-H. Jeong, Y.-D. Seo and E. Lee*, "SEPO-IR: Software-based Evaluation Process for Calculate Infection Rate," Software X, Vol. 30, 2025, p. 102159.
  (2024-JCR-IF: 2.4, JIF PERCENTILE TOP 40.5%)

• K. Jeong, G. Jo, S. Shin, D. Yu, H. Bae, J. Song, S. An, C. Shin, S.-H. Hyun, J.-H. Jeong, and E. Lee, "ConTexT-Net: Multi-Representation Fusion of Contour and Texture Features for Robust White Blood Cell Classification", IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2025**), Wuhan, China, Dec. 15-18, 2025.

• I.-G. Lee, J.-Y. Oh, H. Choi, T.-E. Kam, N. Lee, S.-H. Hyun, E. Lee, J.-H. Jeong*, "EdgeANet: A Transformer-based Edge Representation Learning Network for Canine X-ray Verification," The 28th Medical Image Computing and Computer-Assisted Intervention (MICCAI 2025**), South Korea, Sep. 23-27, 2025. 

• H. Lee†, E. Jo†, M. Lim, Y.-H. Son, B. Kang, H. Nam, J.-H. Jeong, D.-H. Shin, and T.-E. Kam, "Sparse3Diff: A Diffusion Framework for 3D Reconstruction from Sparse 2D Slices in Volumetric Optical Imaging," The 28th Medical Image Computing and Computer-Assisted Intervention (MICCAI 2025**), South Korea, Sep. 23-27, 2025.

• M. Kim, S.-H. Yu, J.-H. Jeong, I. Lee, and W.-G. Son, "Development of a Novel Ensemble Machine Learning Model for Predicting Post-anesthetic Hypoxemia in Mechanically Ventilated Dogs," World Congress of Veterinary Anaesthesia & Analgesia (WCVAA '25), France, Sep. 16-19, 2025.

• S.-W. Kim, H.-Y. Park, I.-G. Lee, S.-N. Jang, S.-H. Yu, J.-Y. Oh, G.-M. Moon, J.-H. Jeong*, “Towards A Lightweight Deep Learning Framework for Real-Time Vital Sign Prediction with RGB Cameras,” Proc. 13th International Winter Conference on Brain-Computer Interface (BCI), South Korea, Feb. 24–26, 2025.

• S.-N. Jang, H.-Y. Park, S.-W. Kim, S.-H. Yu, M. Lee,  J.-H. Jeong*, “Integrated Word2Vec-based Speech Annotations for Enhanced EEG Decoding of Speech Intentions,” Proc. 13th International Winter Conference on Brain-Computer Interface (BCI), South Korea, Feb. 24–26, 2025.

• H.-Y. Park, S.-N. Jang, S.-W. Kim, H. Roh, A.-H. Kim, J.-H. Jeong*, "Attention-based Latent Representation Learning for Cross-Linguistic EEG Decoding," BESK 2025(2025 한국뇌공학회 하계 워크샵), South Korea, July. 10-12, 2025.

• S.-N. Jang, H.-Y. Park, S.-W. Kim, H. Roh, A.-H. Kim, J.-H. Jeong*, "EEG-Based Sentence-Level Imagined Speech Decoding with Temporal Tokenization," BESK 2025(2025 한국뇌공학회 하계 워크샵), South Korea, July. 10-12, 2025.

• H. Roh, S.-N. Jang, H.-Y. Park, S.-W. Kim, J.-H. Jeong*, "Analysis of the Relationship Between Blood Glucose and Physiological Indicators: Implications for Personalized Health Management," KCC 2025(2025 한국컴퓨터종합학술대회), South Korea, July. 2-4, 2025. 

• H.-J. Byon, G.-R. Shin, Y.-Y. Im, H.-Y. Park, J.-H. Jeong*, "CNN-based Real-time Affective System for Facial Expression Recognition in OTT Content Viewing," KCC 2025(2025 한국컴퓨터종합학술대회), South Korea, July. 2-4, 2025. 

• J.-H. Jo, I.-G. Lee, J.-Y. Oh, J.-H. Jeong*, "Development of Active Learning-based Generative Model  for Chest Radiograph in Dog,"  KCC 2025(2025 한국컴퓨터종합학술대회), South Korea, July. 2-4, 2025. 

• M.-S. Kim, S.-H. Yu, J.-H. Jeong*, "A Enhanced Detection of Anomalies in Industrial Machinery Sounds via Cepstrum-Driven Deep Learning Approach,"  KCC 2025(2025 한국컴퓨터종합학술대회), South Korea, July. 2-4, 2025. 

• M.-H. Kim, S.-H. Yu, I.-H. Lee, J.-H. Jeong, W.-G. Son, "Predicting Hypoxemia After Anesthetic Recovery in Dogs Using Machine Learning," KSVC 2025(한국임상수의학회 2025 춘계학술대회), South Korea, May. 17, 2025.

• H.-Y Park, S.-N. Jang, S.-W. Kim, H. Roh, J.-H. Jeong*, "Towards Enhanced Cross-Linguistic Sentence-Level Speech Imagery Decoding through EEG Feature Extraction and Subject-Specific Learning," KOSOMBE 2025(2025 대한의용생체공학회 춘계학술대회), South Korea, May. 8-10, 2025. 

• H. Yu, I.-G. Lee, J.-Y. Oh, T. Lee, J. Kim, J.-H. Jeong*, and K. Eom*, "Deep Learning-Based Ultrasonographic Classification of Canine Chronic Kidney Disease," Frontiers in Veterinary Science, Vol. 11, 2024, pp. 1-8.

(2023-JCR-IF: 2.6, JIF PERCENTILE TOP 13.1%)

• M. Lee, H. Kang, S.-H. Yu, H. Cho, J. Oh, G. Lande, O. Gosseries, J.-H. Jeong*, “Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 32, 2024, pp. 2533-2544.
  (2023-JCR-IF: 4.8, JIF PERCENTILE TOP 2.9%)

• M. Lee, H.-Y. Park, W. Park, K.-T. Kim, Y.-H. Kim*, and J.-H. Jeong*, “Multi-task Heterogeneous Ensemble Learning-based Cross-Subject EEG Classification under Stroke Patients,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vo. 32, 2024, pp. 1767-1778.
  (2023-JCR-IF: 4.8, JIF PERCENTILE TOP 2.9%)

• J.-H. Jeong, I.-G. Lee, S.-K. Kim, T.-E. Kam, S.-W. Lee*. and E. Lee*, “DeepHealthNet: Adolescent Obesity Prediction System Based on a Deep Learning Framework,” IEEE Journal of Biomedical and Health Informatics, Vol. 24, No. 4, 2024, pp. 2282-2293.
  (2023-JCR-IF: 6.7, JIF PERCENTILE TOP 6.8%)

• J.-M. Kim, K.-S. Heo, D.-H. Shin, H. Nam, D.-O. Won, J.-H Jeong, and T.-E. Kam*, “A Learnable Continuous Wavelet-based Multi-Branch Attentive Convolutional Neural Network for Spatio-Spectral-Temporal EEG Signal Decoding,” Expert Systems with Applications, Vol. 251, 2024, pp. 123975.
  (2023-JCR-IF: 7.5, JIF PERCENTILE TOP 5.6%)

• D.-J. Lee, D.-H. Shin, Y.-H. Son, J.-W. Han, J.-H. Oh, D.-H Kim, J.-H. Jeong, and T.-E Kam*, “Spectral Graph Neural Network-based Multi-atlas Brain Network Fusion for Major Depressive Disorder Diagnosis,” IEEE Journal of Biomedical and Health Informatics, Vol. 28, No. 5, 2024, pp. 2967-2978.
  (2023-JCR-IF: 6.7, JIF PERCENTILE TOP 6.8%)

• K.Jeong, M. Kim, G. Cho, H. Oh, J. Jeong, Y. Lee, H. Seo, J.-H. Jeong, D. Yu, H. Bae, S.-H. Hyun, and E. Lee "A Two-stage AI Framework to Detect and Classify White Blood Cells for Supporting Diseases Diagnosis in Veterinary Medicine", IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2024**), Lisbon, Portugal, Dec. 3-6, 2024. 

• J.-Y. Oh, I.-G. Lee, T.-E. Kam, Namsoon Lee, and J.-H. Jeong* "FSS-In: Robust Few-Shot Segmentation with Incremental Noise Learning in Veterinary Radiology," MICCAI 2024** - 3rd Workshop on Applications of Medical AI (AMAI), Marrakesh, Morocco, October 6, 2024.

• H.-Y. Park, S.-Y. Kim, M.-J. Lee, and J.-H. Jeong* "Lesions Prediction in Post-stroke Patients Using Delta-to-Alpha Ratios Strategy from EEG Signals," 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2024), Orlando, Florida, USA, July. 15-19, 2024. 

• S.-N. Jang, H.-Y. Park, and J.-H. Jeong* "Towards Neurolinguistic Processing Transformer Using EEG Tokenization for Smart Brain-Computer Interaction," 9th Edition of International Conference on Neurology and Neurological Disorders (Neurology 2024), Paris, France, Jun. 20-22, 2024. 

• I.-G. Lee, J.-Y. Oh, H.-J.Yu, J.-H Kim, K.-D. Eom, and J.-H. Jeong*, "Generative Active Learning with Variational Autoencoder for Radiology Data Generation in Veterinary Medicine," Proc. IEEE International Conference on Artificial Intelligence (CAI), Singapore, Singapore, Jun. 25-27, 2024.

• H.-Y. Park and J.-H. Jeong* "Towards Brain-Computer Interface based Communication Tool utilizing EEG Signals Integrated with Large Language Model," 9th Edition of International Conference on Neurology and Neurological Disorders (Neurology 2024), Paris, France, Jun. 20-22, 2024. 

• H. Oh, K. Jeong, J.-H. Jeong, and E. Lee  "LINK: Self-Adaptive System with Human-Machine Teaming-based Loop for Interoperability in IoT Environments," The 39th ACM/SIGAPP Symposium On Applied Computing (SAC '24**), Avila, Sapin, Apr. 8-12, 2-24. 

• S.-H. Yu, Y.-M. Go, H.-Y. Park, S.-J. Lee, M. Lee, and J.-H Jeong*, “Towards Motor Imagery Classification of Finger Tapping by Both Hands for Controlling a Finger-Arm Bionic Robot,” Proc. 12th International Winter Conference on Brain-Computer Interface (BCI), South Korea, Feb. 26–28, 2024.

• K. Jeong, D.-R. Kim, J.-H. Ryu, H.-W. Kim, J. Cho, E. Lee, J.-H. Jeong*, "A Monitoring System for Cattle Behavior Detection Using YOLO-v8 in IoT Environments," 2024 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NY, USA, Jan. 5-8, 2024. 

• K. Jeong, E. Ko, H. Oh, G. Cho, H. Seo, J. Choi, J.-H. Jeong, E. Lee, "Method to Predict and Explain Taste Preference Using Pork Characteristics and Consumer Information," 2024 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NY, USA, Jan. 5-8, 2024. 

• J.-H. Jeong, B.-H. Kwon, K.-H. Shim, B.-H. Lee, and S.-W. Lee, “Brain-Machine Interface Based Intention Determination Device And Method Using Virtual Environment”,  US 11,914,773, 2024.

• S.-K. Hong, J.-N. Lee, K.-M.Kim, J.-Y. Oh, J.-H. Jeong*, "Method of Deep Learning-Based Music Symbol Detection Using Watershed Algorithm," KCC 2024(2024 한국컴퓨터종합학술대회) , South Korea, Jun. 26-28, 2024. 

• D.-W. Seo, J.-H. Nam, Y.-K. Kim, S.-H. Yu, J.-H. Jeong*, "Exhibition Visitor Trajectory Analysis and Visualization System Using YOLOv5," KCC 2024(2024 한국컴퓨터종합학술대회) , South Korea, Jun. 26-28, 2024. (Participation Prize 🏆)

• S.-W. Kim, E. -S. Lee, Y.-A. Sung, Y.-M. Go, I.-G. Lee, J.-E. Hong, J.-H. Jeong*, "Generating Emotional Expression Images using an Generative Adversarial Networks,"  KCC 2024(2024 한국컴퓨터종합학술대회) , South Korea, Jun. 26-28, 2024.

• J.-H. Jeong, J.-H. Cho, B.-H. Lee, and S.-W. Lee, “Real-Time Deep Neurolinguistic Learning Enhances Non-Invasive Neural Language Decoding for Brain-Machine Interaction,” IEEE Transactions on Cybernetics, Vol. 53, No. 12, 2023, pp. 7469-7482.
  (2023-JCR-IF: 9.4 JIF PERCENTILE TOP 4.7%)

• D.-H. Lee, J.-H. Jeong, B.-W. Yu, T.-E. Kam, and S.-W. Lee, "Autonomous System for EEG-based Multiple Abnormal Mental States Classification Using Hybrid Deep Neural Networks Under Flight Environment," IEEE Trans. Systems, Man and Cybernetics: Systems, Vol. 53, No. 10, 2023, pp. 6426-6437.
  (2023-JCR-IF: 8.6, JIF PERCENTILE TOP 5.3%)

• H.-J. Ahn, D.-H. Lee, J.-H. Jeong, S.-W. Lee., “Multiscale Convolutional Transformer for EEG Classification of Mental Imagery in Different Modalities,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 31, 2023, pp. 646 - 656.
  (2023-JCR-IF: 4.8, JIF PERCENTILE TOP 2.9%)

• S.-H. Yu, H.-Y Park, S.-J Lee, and  J.-H. Jeong*, "Sentence-Level Neural Language Decoding based on Speech Imagery from EEG Signals," Journal of Korean Institute of Information Technology, Vol. 21, No. 8, 2023, pp. 153-164.

• J.-Y. Oh, I.-G Lee, Y.-M Go, E. Lee, and  J.-H. Jeong*, "Leveraging Image Classification and Semantic Segmentation for Robust Cardiomegaly Diagnosis in Pet," Journal of Korean Institute of Information Technology, Vol. 21, No. 8, 2023, pp. 143-152.

• Y.-M. Go, H.-B. Seo, H.-Y. Park, E. Lee, J.-H. Jeong*, "Development of Container Loss Risk Automatic Detection System Based on Deep Learning Framework," KSC 2023(정보과학회 2023 한국소프트웨어 종합학술대회), South Korea, Dec. 20-22, 2023. 

• I.-G. Lee, J.-Y. Oh, and J.-H. Jeong*, "Autoencoder-Based Generative Active Learning for Robust Canine Thoracic Radiograph Augmentation," IEEE, 2023 IEEE Seoul Section Student Paper Contest, South Korea, Dec. 02, 2023. 

• S.-H. Yu, Y.-M. Go, and J.-H. Jeong*, "Optimizing Factory Sound Data via Cepstral-based Deep Learning Framework for Robust Machinery Anomaly Detection," IEEE, 2023 IEEE Seoul Section Student Paper Contest, South Korea, Dec. 02, 2023. 

• J.-Y. Oh, I.-G. Lee, H.-H. Chang, E.Lee, and J.-H. Jeong*, "Application of A Dual-Stage Deep Learning Framework to Detect Left Atrial Enlargement for Pet Heart Failure," Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Hawaii, USA, Oct. 1-4, 2023. 

• H.-Y. Park, S.-H. Yu, S.-J. Lee, and J.-H. Jeong*, "Speech Imagery Decoding for Emotional Expression by Exploring Visual Perception from EEG Signals," Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Hawaii, USA, Oct. 1-4, 2023. 

• S.-H. Yu, H.-Y. Park, S.-J. Lee, and J.-H. Jeong*, "EEG Classification of Speech Imagery Paradigm Based on A Subject-Dependent Spectral Filtering," 44th Annual International Conference on the IEEE Engineering in Medicine and Biology Society (EMBC), Sydney, Australia, Jul. 24-28, 2023. 

• J.-H. Jeong* and K.-T. Kim "Brain-machine teaming: Recent advances for neural language decoding from EEG signals," 7th Edition of International Conference on Neurology and Neurological Disorders, Rome, Italy, Jun. 16-17, 2023. 

• J.-H. Cho†, J.-H. Jeong†, and S.-W. Lee, “NeuroGrasp: Real-Time EEG Classification of High-Level Motor Imagery Tasks Using A Dual-Stage Deep Learning Framework,” IEEE Transactions on Cybernetics, Vol. 52, No. 12, 2022, pp. 13279-13292.
  (2023-JCR-IF: 9.4 JIF PERCENTILE TOP 4.7%)

• 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, 2022, Vol 16, 2022, pp.898300.
  (2023-JCR-IF: 2.4, JIF PERCENTILE TOP 39.1% )

• D.-Y. Lee†, J.-H. Jeong†, B.-H. Lee, and S.-W. Lee, “Motor Imagery Classification Using Inter-Task Transfer Learning via A Channel-Wise Variational Autoencoder-based Convolutional Neural Network,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 30, 2022, pp. 226-237.
  (2023-JCR-IF: 4.8, JIF PERCENTILE TOP 2.9%)

• T.-H. Park, J.-Y. Oh, E. Lee, and J.-H. Jeong*, "Recognition of Pet Heart Failure Using Dual-stream Convolutional Neural Network," Journal of Research Institute for Computer and Information Communication, Vol. 30, No. 2, 2022, pp. 31-25.

• H.-Y. Park, S.-H. Yu, and J.-H. Jeong*, "Towards Brain to Computer Bidirectional Interface Based on Speech Imagery Decoding from EEG Signals," Journal of Research Institute for Computer and Information Communication, Vol. 30, No. 2, 2022, pp. 37-40.

• I.-G. Lee, M.-S. No, E. Lee, and J.-H. Jeong*, "Robust Body Mass Index Prediction of Adolescents Based on Long Short-term Memory Network," Journal of Research Institute for Computer and Information Communication, Vol. 30, No. 2, 2022, pp. 25-29.

• S.-H. Yu, H.-Y. Park, and J.-H. Jeong*, "Recognizing Drowsiness States from EEG Signals Based on Temporal-Spatio Convolutional Neural Networks," Journal of Research Institute for Computer and Information Communication, Vol. 30, No. 2, 2022, pp. 41-45.

• J.-Y. Oh, T.-H. Park, E. Lee, J.-H. Jeong*, "Cardiac Recognition and Abnormal Detection of Pet Heart Failure Using Dual-Stage YOLOv5," ACK 2022(한국정보처리학회 추계학술대회), South Korea, Nov. 3-5, 2022. (Silver Prize 🏆)

• S.-H. Yu, H.-Y. Park, E. Lee, J.-H. Jeong*, "Drowsiness Classification using Convolutional Neural Network based on Electroencephalography Signals," ACK 2022(한국정보처리학회 추계학술대회), South Korea, Nov. 3-5, 2022. (Bronze Prize 🏆)

• H.-Y. Park, S.-H. Yu, E. Lee, J.-H. Jeong*, "Neural Language Decoding based on Speech Imagery Paradigm for Intuitive Brain-Computer Interface," ACK 2022(한국정보처리학회 추계학술대회), South Korea, Nov. 3-5, 2022.

• M.-S. No, I.-G. Lee, E. Lee, J.-H. Jeong*, "Classification of Body Mass Index Degree Based on Deep Neural Network for Digital Healthcare," ACK 2022(한국정보처리학회 추계학술대회), South Korea, Nov. 3-5, 2022.

• D.-Y. Kim, D.-K. Han, J.-H. Jeong, and S.-W. Lee, "EEG-based Driver Drowsiness Classification via Calibration-Free Framework with Domain Generalization," Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Prague, Czech Republic, Oct. 9-12, 2022. 

• S. Musellim, D.-K. Han, J.-H. Jeong, and S.-W. Lee, "Prototype-Based Domain Generalization Framework for Subject-Independent Brain-Computer Interfaces," has been accepted for publication in the 44th Annual International Conference on the IEEE Engineering in Medicine and Biology Society, Glasgow, Scotland, Jul. 11-15, 2022. 

• D.-K. Han, S. Musellim, D.-Y. Kim, J.-H. Jeong*, "Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface,” Proc. 10th International Winter Conference on Brain-Computer Interface (BCI), South Korea, Feb. 21–23, 2022.

• B.-H. Kwon, B.-H. Lee, J.-H. Cho, J.-H Jeong*, “Decoding Visual Imagery from EEG Signals using Visual Perception Guided Network Training Method,” Proc. 10th International Winter Conference on Brain-Computer Interface (BCI), South Korea, Feb. 21–23, 2022.

• M. Lee†, J.-H. Jeong†, Y. Kim, S.-W. Lee, “Decoding Finger Tapping with the Affected Hand in Chronic Stroke Patients during Motor Imagery and Execution,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 29, 2021, pp. 1099-1109. (2023-JCR-IF: 4.8, JIF PERCENTILE TOP 2.9%)

• K. Kim†, J.-H. Jeong†, J.-H. Cho†, S. Kim, J. Kang, J. Ryu, S.-W. Lee, “Development of Human-Display Interface with Vibrotactile Feedback for a Real-World Assistive Application,” Sensors, Vol. 21, No.2, 2021, pp. 592-608.
  (2023-JCR-IF: 3.4, JIF PERCENTILE TOP 32.0%)

• D.-H. Lee, D.-K. Han, S.-J. Kim, J.-H. Jeong, and S.-W. Lee, “Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks,” Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Melbourne, Australia, Oct. 17–20, 2021 (Oral Presentation).

• J.-S. Bang, and J.-H. Jeong, and D.-O. Won, “Classification of Visual Perception and Imagery based EEG Signals Using Convolutional Neural Networks,” Proc. 9th International Winter Conference on Brain-Computer Interface (BCI), Korea, Feb. 22–24, 2021 (Oral Presentation).

• D.-K. Han and J.-H. Jeong*, “Domain Generalization for Session-Independent Brain-Computer Interface,” Proc. 9th International Winter Conference on Brain-Computer Interface (BCI), Korea, Feb. 22–24, 2021.

• J.-H. Cho, J.-H. Jeong, M.-K. Kim, and S.-W. Lee, “Towards Neurohaptics: Brain-Computer Interfaces for Decoding Intuitive Sense of Touch,” Proc. 9th International Winter Conference on Brain-Computer Interface (BCI), Korea, Feb. 22–24, 2021.

• B.-H. Lee, J.-H. Jeong, and S.-W. Lee, “Non-Parametric Inference based Label Noise Score Estimation for Brain-Computer Interface,” 2021 The Summer Workshop of Brain Engineering Society of Korea, Korea, Aug. 19–20, 2021.

• B.-H. Kwon, J.-H. Jeong, and S.-W. Lee, “Visual Imagery Classification with Deep Neural Network based on Functional Connectivity,” 2021 The Summer Workshop of Brain Engineering Society of Korea, Korea, Aug. 19–20, 2021.

• J.-H. Jeong, K.-H. Shim, D.-J. Kim, and S.-W. Lee, “Brain-Controlled Robotic Arm System based on Multi-Directional CNN-BiLSTM Network using EEG Signals,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 28, No.5, 2020, pp. 1226-1238.
  (2023-JCR-IF: 4.8, JIF PERCENTILE TOP 2.9%)

• J.-H. Jeong, N.-S. Kwak, C. Guan, and S.-W. Lee, “Decoding Movement-Related Cortical Potentials based on Subject-Dependent and Section-Wise Spectral Filtering,” IEEE Transactions on Neural Systems & Rehabilitation Engineering, Vol. 28, No. 3, 2020, pp. 687-698.
  (2023-JCR-IF: 4.8, JIF PERCENTILE TOP 2.9%)

• J.-H. Jeong, J.-H. Cho, K.-H. Shim, B.-H. Kwon, B.-H. Lee, D.-Y. Lee, D.-H. Lee, and S.-W. Lee, “Multimodal Signal Dataset for 11 Intuitive Movement Tasks from Single Upper Extremity during Multiple Recording Sessions,” GigaScience, Vol. 9, No. 10, 2020, pp. 1-15.
  (2023-JCR-IF: 11.8, JIF PERCENTILE TOP 7.4%)

• J.-H. Jeong, B.-H. Lee, D.-H. Lee, Y.-D. Yun, and S.-W. Lee, “EEG Classification of Forearm Movement Imagery Using A Hierarchical Flow Convolutional Neural Network,” IEEE Access, Vol. 8, 2020, pp. 66941-66950.
  (2023-JCR-IF: 3.4, JIF PERCENTILE TOP 34.9%)

• D.-H. Lee†, J.-H. Jeong†, K. Kim, B.-W. Yu, and S.-W. Lee, “Continuous EEG Decoding of Pilots' Mental States using Multiple Feature Block-based Convolutional Neural Network,” IEEE Access, Vol. 8, 2020, pp. 121929-121941.
  (2023-JCR-IF: 3.4, JIF PERCENTILE TOP 34.9%)

• B.-H. Lee†, J.-H. Jeong†, S.-W. Lee, “SessionNet: Feature Similarity-based Weighted Ensemble Learning for Motor Imagery Classification,” IEEE Access, Vol. 8, 2020, pp. 134524-134535.
  (2023-JCR-IF: 3.4, JIF PERCENTILE TOP 34.9%)

• J.-H. Cho, J.-H. Jeong, and S.-W. Lee, “Decoding of Grasp Motions from EEG Signals Based on a Novel Data Augmentation Strategy,” 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Montreal, Canada, July 20–24, 2020 (Oral Presentation).

• J.-H. Cho, J.-H. Jeong, D.-J. Kim, and S.-W. Lee, “A Novel Approach to Classify Natural Grasp Actions by Estimating Muscle Activity Patterns from EEG Signals,” Proc. 8th International Winter Conference on Brain-Computer Interface (BCI), Korea, Feb. 26–28, 2020 (Oral Presentation).

• J.-H. Jeong, D.-H. Lee, H.-J. Ahn, and S.-W. Lee, “Towards Brain-Computer Interfaces for Drone Swarm Control,” Proc. 8th International Winter Conference on Brain-Computer Interface (BCI), Korea, Feb. 26–28, 2020.

• B.-H. Lee, J.-H. Jeong, K.-H. Shim, and S.-W. Lee, “Classification of High-Dimensional Motor Imagery Tasks based on An End-to-End Role Assigned Convolutional Neural Network,” Proc. 45th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 4–8, 2020.

• D.-Y. Lee, J.-H. Jeong, K.-H. Shim, and S.-W. Lee, “Decoding Movement Imagination and Execution from EEG Signals Using BCI-Transfer Learning Method Based on Relation Network,” Proc. 45th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 4–8, 2020.

• B.-H. Kwon, J.-H. Jeong, J.-H. Cho, and S.-W. Lee, “Decoding of Intuitive Visual Motion Imagery Using Convolutional Neural Network under 3D-BCI Training Environment,” Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Toronto, Canada, Oct. 11–14, 2020.

• S.-B. Lee, H.-J. Kim, H. Kim, J.-H. Jeong, S.-W. Lee, and D.-J. Kim, “Comparative Analysis of Features Extracted from EEG Spatial, Spectral and Temporal Domains for Binary and Multiclass Motor Imagery Classification,” Information Sciences, Vol. 502, 2019, pp. 190-200.
  (2022-JCR-IF: 8.1, JIF PERCENTILE TOP 8.2%)

• J.-H. Jeong, K.-H. Shim, D.-J. Kim, and S.-W. Lee, “Trajectory Decoding of Arm Reaching Movement Imageries for Brain-Controlled Robot Arm System,” 2019 41th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Berlin, Germany, July 23–27, 2019 (Oral Presentation).

• S.-H. Lee, M. Lee, J.-H. Jeong, and S.-W. Lee, “Towards an EEG-based Intuitive BCI Communication System Using Imagined Speech and Visual Imagery,” Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Italy, Oct. 6–9, 2019 (Oral Presentation).

• K.-H. Shim, J.-H. Jeong, B.-H. Kwon, B.-H. Lee, and S.-W. Lee, “Assistive Robotic Arm Control based on Brain-Machine Interface with Vision Guidance using Convolution Neural Network,” Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Italy, Oct. 6–9, 2019.

• J.-H. Cho, J.-H. Jeong, K.-H. Shim, and S.-W. Lee, “Classification of Various Grasping Tasks based on Temporal Segmentation Method Using EEG and EMG Signals,” Proc. of 8th Graz Brain-Computer Interface Conference (GBCIC), Graz, Austria, Sep. 16–20, 2019.

• Y.-D. Yun, J.-H. Jeong, J.-H. Cho, D.-J. Kim, and S.-W. Lee, “Reconstructing Degree of Forearm Rotation from Imagined movements for BCI-based Robot Hand Control,” 2019 41th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Berlin, Germany, July 23–27, 2019.

• Y.-D. Yun, J.-H. Jeong, and S.-W. Lee, “Decoding of Imagined Forearm Rotation for Brain-Machine Interface Driven Robot Hand Control,” 2019 Symposium of Brain and Artificial Intelligence, Korea, Feb. 21–23, 2019.

• B.-W. Yu, J.-Y. Kim, J.-H. Jeong, T. Oh, H.-S. Yoon, and S.-W. Lee, “Pilot’s Drowsiness Prediction using Multi-variate Linear Regression based on Physiological Signals,” 2019 Symposium of Brain and Artificial Intelligence, Korea, Feb. 21–23, 2019.

• B.-W. Yu, J.-H. Jeong, D.-H. Lee, and S.-W. Lee, “Detection of Pilot’s Drowsiness Based on Multimodal Convolutional Bidirectional LSTM Network,” Lecture Notes in Computer Science(LNCS), Proc. Asian Conference on Pattern Recognition, Springer, pp. 530–543, 2019.

• J.-H. Jeong, K.-T. Kim, D.-J. Kim, and S.-W. Lee, “Decoding of Multi-Directional Reaching Movements for EEG-based Robot Arm Control,” Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, Aug. 7–10, 2018 (Oral Presentation).

• J.-H. Cho, J.-H. Jeong, K.-H. Shim, D.-J. Kim, and S.-W. Lee, “Classification of Hand Motions within EEG Signals for Non-Invasive BCI-based Robot Hand Control,” Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, Aug. 7–10, 2018 (Oral Presentation).

• M. Lee, B. Baird, O. Gosseries, J.-O. Nieminen, J.-H. Jeong, G. Tononi, and S.-W. Lee, “Classification of Sleep Consciousness based on Filter Bank Common Spatial Pattern,” Proc. of International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI), Montreal, Canada, May 13–17, 2018 (Oral Presentation).

• J.-H. Jeong, K.-T. Kim, Y.-D. Yun, S.-W. Lee, “Design of a Brain-Controlled Robot Arm System based on Upper-Limb Movement Imagery,” Proc. 6th International Winter Conference on Brain-Computer Interface (BCI), Korea, Jan. 15–17, 2018.

• K.-T. Kim, J.-H. Jeong, and S.-W. Lee, “Brain-Inspired Artificial Intelligence and Brain Engineering,” Communications of the Korean Institute of Information Scientists and Engineers, Vol. 36, No. 1, pp. 27–32, 2018.

• J.-H. Jeong, M.-H. Lee, N.-S. Kwak, and S.-W. Lee, “Decoding of Walking Intention Under Lower Limb Exoskeleton Environment Using MRCP Feature,” Proc. of 7th Graz Brain-Computer Interface Conference (GBCIC), Graz, Austria, 18–22, 2017 (Oral Presentation).

• J.-H. Jeong, M.-H. Lee, N.-S. Kwak, and S.-W. Lee, “Single-Trial Analysis of Readiness Potentials for Lower Limb Exoskeleton Control,” Proc. 5th International Winter Conference on Brain-Computer Interface (BCI), Korea, Jan. 9–11, 2017 (Oral Presentation).

• J.-H. Jeong, N.-S. Kwak, and S.-W. Lee, “A Single-Trial EEG Analysis for User-Dependent Robotic Exoskeleton Control,” 2017 Summer Workshop of Brain and Artificial Intelligence, Korea, July 6–8, 2017.

• J.-H. Jeong, N.-S. Kwak, M.-H. Lee, and S.-W. Lee, “Analysis of Movement-Related Cortical Potentials for a Lower Limb Exoskeleton Control,” 2017 Symposium of Brain and Artificial Intelligence, Korea, Feb. 8–10, 2017.

• J.-H. Jeong, N.-S. Kwak, and S.-W. Lee, “Towards Detecting of Walking Intention from Readiness Potentials for a Powered Exoskeleton Control,” Proc. 6th International Brain-Computer Interface Meeting, California, USA, May 30–Jun. 3, 2016.

• M.-H. Lee, K.-T. Kim, Y.-J. Kee, J.-H. Jeong, S.-M. Kim, S. Fazli, and S.-W. Lee, “OpenBMI: A Real-Time Data Analysis Toolbox for Brain-Machine Interfaces,” Proc. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary, Oct. 9–12, 2016.

• J.-H. Jeong, M.-H. Lee, and S.-W. Lee, “Walking Intention Analysis based on Readiness Potentials for Lower Limb Exoskeleton Control,” Korea Computer Congress, Communications of the Korean Institute of Information Scientists and Engineers, Korea, June 29–July 1, 2016.