Bo’s research explores the intersection of multimodal perception and efficient deep learning. They develop methods for associating and reconstructing information across vision and wireless sensing, including vision–phone multimodal association and real-world multimodal reconstruction, with the goal of enabling robust visual navigation in complex environments. Complementing this, Bo focuses on efficient neural networks, particularly on model selection for few-class settings and model merging for scalable edge computing.