Our lab aims to help understanding and implement human intelligence for most common communication media: vision, natural language, and speech. Since they are connected and correlated to each other, we work on developing effective and efficient machine learning models for multi-modalities.
In the Interactive Multimodal Machine Learning Lab lab, we are interested in Machine Learning and applications to Computer Vision and Language Processing. Specifically, we work on Multimodal Learning, Generative Models, and Deep Learning and our research topics include (but not limited to) Multimodal LLM (Vision-Language Model), Embodied AI/Vision Language Action Model, Text-to-image generation, Multi-modal conversational models, Video understanding and question answering, and Explainable AI. Additionally, we are also work on AI for Science.