• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    January 09, 2019: Prof. Huynh Huu Tue (AVITECH, Canada), What is exactly Industrial Internet of Things (IIoT)? How does it affect Vietnam?

    Based on the robust and rapid development of data transmission networks and high performance information processing algorithms for large data sets, the modern production industry has made great progresses over the last few decades. These developments are driven by modern industrial backgrounds into a condition known as the 4.0 industrial revolution, or for a shorter name “Industry 4.0” Industrial 4.0 is essentially a construction and organizational management of a modern manufacturing plant using the knowledge in the areas of “Artificial intelligence”, “Internet” and of “Big data”. Industrial 4.0 design factories and build production lines, based on the “Interconnectivity”, “Automation”, “Machine learning” and “Real time data” (Data exchange and processing in real time). These characteristics correspond to the image of intelligent equipment and devices interacted between them or with people and fully connected to Internet; due to this image, the Industry 4.0 is also known as the “Industrial Internet of Things” (IIoT) or “Smart manufacturing”. In general, Industry 4.0 combines the personnel team, physical production with operations using smart digital technology, learning machine and big data in order to create a well-manageable ecosystem such that Manufacture and management of supply chain would be of high performance. In this talk, we will present concepts, structures and some illustrating examples to help the audience to better understand what is happening in Industry 4.0; we discuss issues that Industry 4.0 would cause for the world, including companies, workers and governments. Finally, we also examine the way Industry 4.0 will affect Vietnam’s higher education and Vietnam’s economy.

    Speaker: Prof. Huynh Huu Tue, AVITECH

    Time: 15:30, Wednesday, January 09, 2019

    Venue: 212-E3, 144 Xuan Thuy, Cau Giay, Hanoi


    Huu Tue Huynh was on the Faculty of Electrical and Computer Engineering of Laval University (Canada) during the period 1969-2005. He became President of the International Bac-Ha University (Vietnam) in 2007 and is now an adjunct professor of the School of Electrical Engineering at the VNU-HCM International University. In 1984, he was an invited guest at AT&T Information Systems in Neptune, New Jersey, and has been invited to give lectures at several universities in Europe, America, and in Asia. Professor Huynh is author and co-author of two books and more than 200 papers and research reports on information processing. He has served as a consultant to a number of Canadian government agencies and industries. His research interests cover stochastic simulation techniques, information processing, fast algorithms, with applications to finance and to 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, […]