• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    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, visual, and text concurrently. First, they assume only one modality can be missing, overlooking scenarios where multiple modalities may be absent simultaneously. Additionally, the deep semantic interactions between modalities at the feature level have not been thoroughly explored. To address these challenges, this paper proposes a novel framework, Mi-CGA, tailored for incomplete multimodal learning in conversational contexts. The backbone component, i.e., Cross-modal Graph Attention Network (CGA-Net), is to extract rich information from conversational graphs in the context of incomplete modality. It consists of three key modules: reconstruction of missing data with Modality Feature Estimation, improving data understanding with the Graph Attention Network, and enhancing cross-modal relationships with the Cross-modal Attention Network, leading to better multimodal emotion recognition performance. Extensive experiments on benchmark datasets consistently demonstrate that Mi-CGA outperforms several representative baseline models, marking a significant advancement in Multimodal ERC.

    Speaker: Dr. Le Duc Trong, FIT-UET

    Time: 15:00, Thursday, January 11, 2024

    Venue: Room 405 E3

    Dr. Duc-Trong Le is currently the Deputy Head of Computer Science department, Faculty of Information Technology (FIT), University of Engineering and Technology, Vietnam National University, Hanoi (VNU-UET). He received the Bachelor in IT from (VNU-UET) in 2011 and earned his Ph.D. in Information Systems from Singapore Management University, Singapore, in 2019. His research interests include Web/Text Mining, Recommendation Systems, Multimodal Learning and Reliable AI. He is the author, and co-author of more than 20 scientific articles that appeared in top-tier conferences such as IJCAI, AAAI, EMNLP, ACM MM, COLING, ECML-PKDD. He is also serving as Reviewer for AI conferences namely IJCAI, AAAI, and Q1 journals including TKDE, TKDD, TITS, NEUCOM. Additionally, he is the principal investigator or researcher in various AI research projects on Reliable AI (QG23.37), Medical AI (KC4.0-40\19-25), Environmental AI (VinIF.2023.DA019) and Behavioral AI (VinIF.2022.DA0087). More details about his research and teaching works are available at https://sites.google.com/view/trongld
    This seminar is jointly organized with the Department of Computer Science, the Institute for Artificial Intelligence, and the Human-Machine Interface Laboratory, VNU University of Engineering and Technology.


    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

    A research overview of ongoing research projects, especially focusing on two that are most related to the VinUni-UIUC Smart Health Center: (1) Misinformation Detection and Trustworthy Large Language Models; (2) Joint Natural Language and Molecule Learning for Drug Discovery. Unsurprisingly these two seemingly different research problems can be tackled with a unified approach based on […]

    January 11, 2024: Prof. Mérouane Debbah (Khalifa University of Science and Technology, UAE) TelecomGPT: The Next Big Wave in Telecomunications

    The evolution of generative artificial intelligence (GenAI) constitutes a turning point in reshaping the future of technology in different aspects. Wireless networks in particular, with the blooming of self-evolving networks, represent a rich field for exploiting GenAI and reaping several benefits that can fundamentally change the way how wireless networks are designed and operated nowadays. […]