Wenbo Lu is a Ph.D. student in Computer Science advised by Professor Shengjie Wang. Prior to his doctoral studies, he earned his B.S. degree with Honors in Data Science from NYU Shanghai. His research interests lie in efficient AI, robotics, and diffusion models, with a particular focus on developing generalizable data-efficient Vision-Language-Action (VLA) models for manipulation tasks.
Publications
- Lu, Wenbo; Zheng, Shaoyi; Xia, Yuxuan; and Wang, Shengjie. “ToMA: Token Merge with Attention for Diffusion Models.” Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025. Poster.
Research Interests
- Vision-Language-Action (VLA) models
- Efficient AI
- Diffusion Models