• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    June 23, 2021: Mr. Nguyen Van Ly (San Diego State Univ., US), Fisher Information Neural Estimation

    Fisher information is a well-known and well-defined concept in mathematical statistics. There are many areas in which the Fisher information is applied to, e.g., estimation theory, Bayesian statistics, frequentist statistics, optimal experimental design, computational neuroscience, physical laws, and machine learning. Therefore, the estimation of Fisher information is of critical importance. In this talk, we introduce a machine learning-based Fisher information estimation method, referred to as Fisher Information Neural Estimation (FINE). Most existing methods for Fisher information estimation rely on the estimation of the underlying distribution, which is not always possible. The proposed FINE method directly estimates the Fisher information based on the observed data. We also show via numerical examples that the proposed FINE method not only outperforms an existing method but also has a lower computational complexity.

    Speaker: Mr. Nguyen Van Ly, San Diego State Univ.

    Time: 15:30, Wednesday, June 23, 2021

    Venue: Webinar; Access code: https://bit.ly/3zKq0W2


    Nguyen Van Ly received the B.Eng. degree in Electronics and Telecommunications from the University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam in 2014, and the M.Sc. degree in Advanced Wireless Communications Systems from CentraleSupélec, University of Paris-Saclay, France in 2016. Since August 2017, he has been a Ph.D. student in a joint doctoral program in computational science between San Diego State University and University of California, Irvine, CA, USA. His research interests include wireless communications, signal processing, and machine learning.


    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, […]