Seminars

December 29, 2020: Dr. Nguyen Viet Dung (ENSTA Bretagne, Brest, France), Telecommunication: Aeronautical mobile and a ground station

Transmission among aeronautical systems and ground stations are of a major importance for numerous operational configurations. The International Telecommunication Union (ITU) officially recommends a model mainly based on the IF-77 electromagnetic wave propagation model. However, French team at ITU showed some drawbacks of the proposed model related to ITU recommendations P.525 and P.526 for areas of high reliefs. In this talk, we summarize key ideas in the IF-77 model and potential problems of using only single-knife edge diffraction in the model. We then propose several approaches to tackle this problem. We conclude this talk by discussing several research directions we aim to conduct in a future work.

Speaker: Dr. Nguyen Viet Dung, ENSTA Bretagne, Brest

Time: 15:30, Tuesday, December 29, 2020

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

NGUYEN Viet-Dung received the B.Sc. in Electronics and Telecommunication Engineering from VNU University of Engineering and Technology (Vietnam), in 2009, M.Sc. in Network and Telecommunication from L’École normale supérieure (ENS) de Cachan, Université Paris XI, in 2012, and Ph.D. in Signal Processing from University of Orléans (France) in 2016. He is now a postdoc at Lab-STICC, UMR 6285 CNRS ENSTA Bretagne, Brest, France and head of Tools for Complex Systems group, VNU-UET-AVITECH, Hanoi, Vietnam. His current research interests include: wireless communication and propagation, matrix and tensor analysis, adaptive signal processing, blind source separation, array signal processing, and statistical performance analysis.

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

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, […]