On August 12, 2026, at VNUHCM–University of Science, Doctoral Researcher Huỳnh Quốc Việt successfully defended his doctoral thesis at the institutional level in Engineering Physics, entitled “Integration of Machine Learning Methods and Neural Networks for Electroencephalogram (EEG) Signal Classification.”
Under the supervision of Assoc. Prof. Huỳnh Văn Tuấn, the dissertation focuses on the integration of signal processing, machine learning, and deep learning techniques to improve the performance of electroencephalogram (EEG) signal classification. The research contributes to the broader application of artificial intelligence in biomedical signal analysis and healthcare, particularly in addressing the challenges associated with complex and highly variable EEG data.
A key contribution of the dissertation is the development of an integrated methodological framework that simultaneously leverages temporal, frequency-domain, time–frequency, and spatial features of EEG signals. Within this framework, the study develops and evaluates a range of advanced models and approaches, including 3D-CNN–LSTM, CNN–LSTM–P, Directed Connected Layer (DCL), Multi-Input CNN–ANN, the CRMT training strategy, and EEG-TAGAN.
These approaches are designed to enhance feature representation and learning, training stability, and classification performance, particularly when dealing with EEG datasets characterized by substantial noise and high variability. The proposed methods were evaluated across multiple EEG datasets, demonstrating their potential to improve EEG signal classification and providing a foundation for further research in deep learning, generative modeling, domain adaptation, and EEG signal processing.
The research outcomes also reflect the strong scientific productivity achieved throughout the doctoral program, with publications in internationally recognized journals and conferences indexed by major academic databases.
Notably, Doctoral Researcher Huỳnh Quốc Việt is the first doctoral candidate in the Engineering Physics program to successfully defend a doctoral thesis. His institutional-level defense therefore represents more than the culmination of an intensive postgraduate research journey; it marks an important milestone in the development of doctoral education and research capacity within the Engineering Physics program.
This achievement also highlights the program’s commitment to fostering interdisciplinary research and the integration of advanced technologies, particularly artificial intelligence, machine learning, and deep learning, into contemporary Engineering Physics research.
The Faculty of Physics and Engineering Physics extends its warmest congratulations to Dr. Huỳnh Quốc Việt on this significant academic achievement. We wish him continued success in his future research, teaching, and academic endeavors, and look forward to his continued contributions to the advancement of Engineering Physics and interdisciplinary scientific research.