Our research group focuses on multimodal computing technology, dedicated to extensive and in-depth exploration and application in various fields based on specific needs. In the area of knowledge reasoning, we concentrate on tasks related to artificial intelligence reasoning and human-like intelligence, with particular attention to various reasoning theories such as mathematical logic, knowledge representation, description logic, and causal reasoning, as well as the integration of these theories into deep learning applications. Our primary research direction is the application of commonsense, logical, and causal reasoning methods in vision-text modalities, aiming to enhance the intelligence and accuracy of multimodal data processing. In the domain of interpretable reasoning in deep learning, we investigate prototype-based case reasoning training methods to promote the credible and understandable application of AI models. Accumulating relevant multimodal computing technologies, we also apply them to the field of mobile computing. This includes research on mobile ad hoc networks, sensor networks, the Internet of Things (IoT), indoor positioning technologies, video compression and reliable transmission technologies based on wireless networks, communication and image processing technologies based on compressed sensing, fall detection technologies, and more, striving to improve the performance and application scope of mobile computing.