• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    May 07, 2019: Prof. Mouloud Adel (Aix-Marseille Univ., France), Some Aspects of Computer-aided Diagnosis Applied on Medical Images

    Medical diagnosis is a very important medical daily task. Doctors need computer-aided tools to help them in analyzing a huge amount of data. Image processing and machine learning can take into account the variability of these data ad provide doctors with efficient and automatic tools. This talk will focus on different approaches that have been successfully applied on optical retinal images to segment the retinal vascular tree, breast X-ray images to segment anatomical regions of interest on mammographic images and Positron Emitting Tomography brain images for Alzheimer’s disease classification.

    Speaker: Prof. Mouloud Adel, Aix-Marseille Univ.

    Time: 15:30, Tuesday, May 07, 2019

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


    Mouloud Adel received his Engineering degree in electrical engineering from the Ecole Nationale Supérieure d’Electricité et de Mécanique (ENSEM) of Nancy, France, as well as his Master’s degree in electronic and feedback control systems in 1990. He obtained his PhD degree from the Institut National Polytechnique de Lorraine (INPL) of Nancy in 1994 in image processing. He has been a Professor Assistant at the Institut Universitaire de Technologie de Marseille since 1994. In 2008 he obtained his HDR from Aix-Marseille University and became an Associate Professor. Since September 2014 he is a full Professor at Aix-Marseille University, France, in Computer Science and Electrical Engineering. He is a member of the Multidimensional Signal Group of Institut Fresnel UMR-CNRS 7249. His research areas concern signal and image processing applied to biomedical and industrial images. He has published more than 50 papers including International journals and conferences articles. He has been involved in many international research programs (Germany, Algeria, United Kingdom). He is a member of the editorial board of Journal of Biomedical Engineering and Informatics. He has been an invited speaker at Polytechnic Institute of Technology of Algiers (Algeria) and at Parma University (Italy), and chaired a special session “Statistical Image Analysis for computer-aided detection and diagnosis on Medical and Biological Images” in IPTA 2014 (IEEE International Conference on Image Processing Theory and Application, Paris). He is the head of the Signal and Image Processing Master of Aix-Marseille University.


    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, […]