Boqi Zhao

Welcome! I am Boqi Zhao, a PhD student in Computer Science at the University of California, Davis. I received my Master of Science in Computer Science from UC Davis in 2025, and later transferred to the CS PhD program in DARE lab, advised by Dr. Junshan Zhang.
My research focuses on robotics learning, particularly in reinforcement learning, imitation learning, world models. I am dedicated to developing robotics systems with advanced generalization capabilities for complex, real-world tasks. I am always open to discussions and collaborations, feel free to contact me.

News

Jul 01, 2025	We present VITA, vision-to-action flow matching policy, which evolves latent images, instead of random Gaussian, to latent actions. VITA is highly efficient because of the conditioning-free and MLP-only architecture.

Education

2025.05 - Present Davis, California, US
University of California, Davis - Ph.D. in Computer Science
2023.09 - 2025.06 Davis, California, US
University of California, Davis - Master of Computer Science
2020.09 - 2023.05 Madison, Wisconsin, US
University of Wisconsin, Madison - Bachelor of Computer Science

Selected Publications

Preprint

VITA: Vision-to-Action Flow Matching Policy

Dechen Gao, Boqi Zhao , Andrew Lee, Ian Chuang, Hanchu Zhou, Hang Wang, Zhe Zhao, Junshan Zhang, and Iman Soltani

2025

arXiv Bib Website PDF

@misc{gao2025vitavisiontoactionflowmatching,
  title = {VITA: Vision-to-Action Flow Matching Policy},
  author = {Gao, Dechen and Zhao, Boqi and Lee, Andrew and Chuang, Ian and Zhou, Hanchu and Wang, Hang and Zhao, Zhe and Zhang, Junshan and Soltani, Iman},
  year = {2025},
  eprint = {2507.13231},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
}