Specialisation in Multimodal Data Analysis

In this course, we will cover state-of-the-art methods and techniques for the integration and interpretation of data within and across modalities. The course will focus on hybrid audio-visual and text models for various multimodal applications using machine learning and deep learning techniques. Actual topics related to multimodal semantic and contextual data analysis and their applications in audio-visual and text domains will be covered and may include but are not limited to: - Multimodal architectures, frameworks, and tools - Multimodal data representation - Embeddings and Transformers - Multimodal data fusion - Semantic and Contextual understanding -- Case study on multimodal sentiment analysis -- Case study on clinical natural language processing -- Case study on speaker identification and recognition

On completion of this course the students will have the following skills, knowledge, and general competence: Knowledge - Possess advanced knowledge within the area of multimodal data analysis - Be able to identify semantic and contextual information across modalities - Become familiar with frameworks and tools - Get acquainted with solutions to challenging applications and open issues Skills - Be able to critically review and analyze existing models - Be able to use and apply relevant methods and techniques across modalities - Be able to propose innovative solutions to assigned problems General Competence - Improved understanding of the domain - Exposure to various tools and techniques - Exposure to open and challenging research topics

We will have seminars using a blended learning approach with a mix of conventional lectures and flipped Classroom and in-class activities. The students will work individually or in groups and are provided with reading material. - There will be lectures by the course instructor and guest lectures by invited experts. - Student/groups presentations on selected topics Compulsory requirements: Each student/group needs to make a short introductory presentation on the topic and provide a detailed presentation of the work at the end of the course. Compulsory assignments Mandatory project report