• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    March 29, 2022: Dr. Vu Thanh Tung (Queen’s Univ. Belfast, UK), Wireless Communication Networks forFederated Learning

    Due to its communication efficiency and privacy-preserving capability, federated learning has emerged as a promising framework for machine learning in 5G-and-beyond wireless networks. Therefore, the novel designs of wireless networks to support the stable and fast operation of federated learning are of great interest. This talk will first highlight the reasons why federated learning becomes important in the future, briefly introduce communication- oriented research directions for realizing federated learning in wireless networks and then discuss state-of-the-art solutions for a massive multiple-input multiple-output (MIMO) network to efficiently support federated learning.

    Speaker: Dr. Vu Thanh Tung, Queen’s Univ. Belfast

    Time: 15:30, Tuesday, March 29, 2022

    Venue: Webinar


    Thanh Tung Vu is currently a Research Fellow at Queen’s University Belfast, UK. His current research interests include applied optimization and machine learning theories in future wireless networks (e.g., massive MIMO, distributed machine learning systems, next-generation satellites). He was the author of the first research work using Cell-free Massive MIMO to support Federated Learning (Top 50 popular papers in Oct-Dec. 2020 of IEEE Transactions on Wireless Communications). He is currently serving as an Editor of Elsevier Physical Communication (PHYCOM). He was an Exemplary Reviewer for IEEE Transactions on Communications in 2021 and IEEE Wireless Communication Letters in 2020 and 2021.


    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: 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, […]