• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    May 05, 2020: Dr. Lam Sinh Cong (AVITECH), Stochastic Geometry Model for Cellular Networks

    Stochastic Geometry Models has been utilized widely to replace Regular Hexagonal Models in terms of cellular network modelling and performance analysis. In this model, the Base Stations (BS) are assumed to be randomly distributed according to a 2D Poisson Point Process while the users follow a specific distribution and have connections to the nearest or strongest BS. Ultra-Dense Network in which the BSs are distributed with ultra-high density is promising a potential network scenario for 5G cellular network systems. This scenario utilizes Fractional Frequency Reuse scheme which allows the BSs fully share their allocated resources with the adjacent cells to improve spectrum efficiency. This talk provides a basic knowledge of Stochastic Geometry Model for Cellular Networks, followed by an application of this model for Ultra-Dense Network.

    Speaker: Dr. Lam Sinh Cong, AVITECH

    Time: 15:30, Tuesday, May 05, 2020

    Venue: Webinar – Microsoft Teams


    Lam Sinh Cong received the Bachelor in Electronics and Telecommunication (Honours) and Master in Electronic Engineering in 2010 and 2012, respectively from University of Engineering and Technology, Vietnam National University (UET, VNUH). He obtained his Ph.D degree in Engineering from University of Technology, Sydney, Australia in 2018. He has been working for UET, VNUH as a lecturer since 2010. His research focuses on Stochastic Geometry Model for Wireless Communications and Machine Learning for Communications.


    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, […]