Yunbo is a Ph.D. student in the Department of Engineering at the University of Cambridge, specializing in data generation in both latent and hyperbolic spaces. His research on tabular data focuses on representing heterogeneous column data in latent space using pre-trained language models and enabling flexible generation of relational data through diffusion-based models. Additionally, he explores conditional generation of heterogeneous data within a shared latent space. For graph data, Yunbo develops data distillation in hyperbolic space to reduce redundancy in large-scale datasets and optimize them for specific machine learning tasks.

Before this, Yunbo completed a MPhil’s degree in Engineering Department at the University of Cambridge, where his research focused on a differential privacy-based personalized clustering federated learning method. Prior to that, he earned a First-Class Honours degree in Engineering from the University of Birmingham, with his undergraduate thesis exploring the application of deep reinforcement learning algorithms for autonomous robotic dismantling tasks.