Son Nguyen obtained his Ph.D. in Computer Science from the University of Twente. His doctoral research focused on adapting, and enhancing Transformer architectures and addressing modality conflicts inherent in existing Multimodal Deep Learning Transformers for different domains, specifically in Indoor Localization and Navigation, where sensing data come from heterogeneous sensor types, such as radio signals representing for spatial changes, and inertial measurement units capturing motion dynamics, each with distinct semantic characteristics. Heading to LARK, he is expected to leverage his transferable expertise to explore modality and architectural instability for uncertainty quantification and estimation in large language models (LLMs), thereby enhancing the quality of LLM-generated infographics, with a particular emphasis on healthcare applications.