• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    April 16, 2019: Dr. Dau Son Hoang (RMIT Australia), Applications of coding theory in distributed storage systems and distributed computing

    In this talk, we discuss recently emerging problems in distributed storage systems and distributed computing where redundant data and redundant computation help to improve the performance of the systems. In the first part of the talk, I will overview different kinds of erasure codes (each code specifies a different method to create data redundancy) proposed in the literature and used in practice, in particular, Reed-Solomon codes (currently employed by Google, Facebook, Quantcast, Baidu, and Hadoop Distributed File System, to name a few), which I have been mainly working on. In the second part, I will introduce the problem of coded distributed computing and go through a few interesting results recently published in the literature. I will also mention briefly some opportunities for pursuing a Ph.D. degree in Australia and so, students who are interested are welcome to the talk.

    Speaker: Dr. Dau Son Hoang, RMIT Australia

    Time: 15:30, Tuesday, April 16, 2019

    Venue: E3-212, 144 Xuan Thuy, Cau Giay, Hanoi


    Dau Son Hoang is currently a lecturer in Computer Science and Information Technology at RMIT University, Australia. He got his bachelor’s degree in Applied Mathematics & Informatics from Vietnam National University, Hanoi, in 2006, and his PhD’s degree in Mathematics from Nanyang Technological University, Singapore, in 2012. He has been working on Coding Theory and Discrete Mathematics for more than ten years and has published 13 papers in reputable journals in these fields such as IEEE Transactions on Information Theory, IEEE/ACM Transactions on Networking, IEEE Transactions on Selected Areas in Communications, Algorithmica, and SIAM Journal on Discrete Mathematics. He is currently the chief investigator of a 3-year DECRA project on advanced coding techniques for fast failure recovery in distributed storage systems, awarded by the Australian Research Council in 2018.


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    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, […]