Multimodal analytics is an interdisciplinary research field focused on the computational analysis and interpretation of data originating from multiple distinct modalities. It investigates the complex relationships, interactions, and synergistic information embedded across diverse data streams (e.g., text, audio, visual, physiological signals) through the development and application of advanced computational methods, often involving machine learning and data fusion techniques. Its significance lies in enabling a more comprehensive understanding of complex phenomena by leveraging complementary information from different sources, leading to enhanced prediction, decision-making, and human-computer interaction capabilities.