IEEE Big Data 2024

Multimodality represents the most effective and comprehensive form of information representation in the real world. Humans naturally integrate various data types, such as text, audio, images, videos, touch, depth, 3D, animations, and biometrics, to make accurate perceptions and decisions. As a result, Our digital world is inherently multimodal. Multimodal data analytics often outperform single-modal approaches in addressing complex real-world challenges. Additionally, the fusion of multimodal sensor data a growing area of interest, particularly for industries like automotive, drone vision, surveillance, and robotics, particularly for industries like automotive, drone vision, surveillance, and robotics, where automation relies on integrating diverse control signals from multiple sources.
The rapid advancement of Big Data technology and its transformative applications across various fields make multimodal Artificial Intelligence (AI) for Big Data a highly relevant and timely topic. This workshop aims to generate momentum around this topic of growing interest, and to encourage interdisciplinary interaction and collaboration between Natural Language Processing (NLP), computer vision, audio processing, machine learning, multimedia, robotics, Human-Computer Interaction (HCI), social computing, cybersecurity, cloud computing, edge compputing, Internet of Things (IoT), and geospatial computing communities. It serves as a forum to bring together active researchers and practitioners from academia and industry to share their insights and recent advancements in this promising area.