• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    May 18, 2021: Dr. Nguyen Phi Le (Hanoi Univ. Sci. Tech.), A Fine-grained AI-based Mobile Air Quality Monitoring and Forecasting

    Recently, with rapid industrialization and urbanization, air pollution is becoming an increasingly painful issue than ever in Vietnam. So far, air monitoring has been carried out by using monitoring stations located at fixed locations. However, due to the cost of installation, deployment, and operation, the number of monitoring stations deployed is often very small. As a result, they only cover a limited area, which is insufficient compared to the actual needs. In this research, we propose a novel air monitoring system that exploits the dynamicity of public vehicles to broaden the air quality monitoring regions. In this talk, we first present the overview of the proposed system and figure out the research problems inside. We also introduce our preliminary at the current stage.

    Speaker: Dr. Nguyen Phi Le, Hanoi Univ. Sci. Tech.

    Time: 15:30, Tuesday, May 18, 2021

    Venue: Webinar; Access code: https://bit.ly/2FkRlae


    Nguyen Phi Le received her B.E. and M.S. degrees from the University of Tokyo in 2007 and 2010, respectively. She received her Ph.D. in Informatics from The Graduate University for Advanced Studies, SOKENDAI, Tokyo, Japan in 2019. Currently, she is an assistant professor at the School of Information and Communication, Hanoi University of Science and Technology, Vietnam. Her research interests include network architectures, applied AI in networking, Internet of Thing networks, mobile edge computing networks, crowdsensing, data mining.


    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, […]