• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    November 12, 2019: Mr. Tran Xuan Tuyen (VNU Univ. Eng. Tech.), Brain network analysis and its applications to brain disorders assessment

    Most of the previous neurotech researches solely concentrate on single neurons within small brain areas rather than analyzing the communication between different regions. The actual brain operation, however, is a high interconnection, so more useful and informative features are acquired only if we take into account the relationships among various sources of brain signals. The theory of network analysis provides an effective tool to investigate the interaction of different areas within the brain, which is modeled as a complex network. This approach has been widely applied to a variety of brain disorder diagnosis. The purpose of this presentation is to provide some basic concepts and state-of-art researches on complex brain network analysis as well as its application to brain disorders assessment.

    Speaker: Mr. Tran Xuan Tuyen, VNU Univ. Eng. Tech.

    Time: 15:30, Tuesday, November 12, 2019

    Venue: G2-315, 144 Xuan Thuy, Cau Giay, Hanoi

    speaker

    Tran Xuan Tuyen received B.Sc. degree in Electronics and Telecommunications from University of Engineering and Technology (UET), Vietnam National University (VNU) in 2019. He is now a research and teaching assistant at the Signal and System laboratory within VNU-UET. His research interests include neurotechnology, machine learning applied to signal processing.

    SAME CATEGORY

    February 2, 2024: Dr. Khoa D. Doan (Vin Univeristy) Toward Reliable and Practical Machine Learning Applications

    While Machine Learning (ML) has rapidly transformed several domains and applications with incredible successes, there are also important areas where the progress is significantly slower. Specifically, there exists a widened complexity gap between the methods currently investigated in research and those used in practice in these areas. One reason is that many algorithms, despite achieving […]

    February 2, 2024: Prof. Heng Ji (University of Illinois at Urbana-Champaign), Combating with Misinformation and Cancer: A Unified Multimodal AI Approach to Healthy and Happy Life

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    January 11, 2024: Dr. Le Duc Trong (FIT-UET) Resilient Multimodal Learning for Multimodal Emotion Recognition in the Presence of Incomplete Modalities

    Multimodal Emotion Recognition in Conversation (Multimodal ERC) is a critical area of research for interpreting human communication in diverse applications. Nevertheless, the persistent issue of uncertain missing modalities poses a major hurdle, hampering the development of robust Multimodal ERC models. Existing approaches face limitations in effectively leveraging a fusion of diverse data modalities encompassing audio, […]