• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    November 17, 2020: Dr. Phan Quoc Huy (Queen Mary Univ. London, UK), Machine learning applied to home-based healthcare monitoring

    The ongoing demographic change has resulted in a large aging population with increased life expectancy in many countries around the world. Consequently, it raises an urgent need for efficient, accessible, cost-effective, and scalable healthcare solutions that can serve a large number of aging people. There is a great opportunity to explore state-of-the-art computational modelling techniques combined with non-invasive, and wearable sensors, actuators and modern communication technologies aimed at transitioning healthcare solutions to home-based environments. The goal is to develop user-friendly wearable devices, new signal processing techniques, and novel machine learning algorithms targeted at home-based health and medical care monitoring applications. This talk will showcase machine learning algorithms applied to acoustic monitoring for sound event detection and to brain-based sleep monitoring with mobile EEG wearable devices. Outlooks on future research in these directions will be also discussed.

    Speaker: Dr. Phan Quoc Huy, Queen Mary Univ. London

    Time: 15:30, Tuesday, November 17, 2020

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


    Huy Phan is a Lecturer in AI at the School of Electronic Engineering and Computer Science, Queen Mary University of London since April 2020 after a postdoc position in the University of Oxford and a Lecturer position at the University of Kent. His research focuses on developing machine learning algorithms for temporal signal analysis, particularly audio/speech analysis and biosignal analysis. He is strongly interested in healthcare applications. Following the Computer Science education at the University of Science at Ho Chi Minh City, Vietnam and the Computer Engineering education at Nanyang Tech. Univ., Singapore, Huy Phan received a PhD degree (Dr.-Ing. in German system) with summa cum laude in Computer Science from the University of Lübeck, Germany. His Ph.D. thesis “Audio event detection, classification, and beyond” was awarded the Bernd Fischer award by the University of Lübeck in 2018.


    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, […]