Experience

Education

• Ph.D in Institute of Software, Chinese Academy of Science, 2018-2024
  • Real-time System, Embedded AI
  • Advisor: Prof. Ying Qiao
• B.S. in School of Computer & Communication Engineering, University Of Science & Technology Beijing, 2014-2018

Work experience

• 2025~ : Xiaomi Robotics Lab
  • Senior Algorithm Engineer
  • Vision Language Action Models (VLA), Agentic AI, Chain-of-Thought, Reinforcement Learning
• 2017~2018: Institute of Automation, Chinese Academy of Sciences
  • Research intern
  • Reinforcement Learning, Game Theory
  • Advisor: Prof. Junliang Xing

Publications

Reinforced Embodied Planning with Verifiable Reward for Real-World Robotic Manipulation

Bo, Z., Hu, Y., Ma, J., Zhou, M., Yin, J., Kang, Y., Liu, Y., Wu, T., Xiang, D., & Chen, H. (2025). Reinforced Embodied Planning with Verifiable Reward for Real-World Robotic Manipulation. arXiv preprint arXiv:2509.25852.

RTDeepEnsemble: Real-time DNN Ensemble Method for Machine Perception Systems

Designing Real-Time Neural Networks by Efficient Neural Architecture Search

BO, Zitong, et al. Designing Real-Time Neural Networks by Efficient Neural Architecture Search. In: International Conference on Intelligent Computing. Singapore: Springer Nature Singapore, 2024. p. 62-73.

HFGCN: Hybrid Filter Graph Convolutional Network for Heterophilic Graphs

BO, Zitong, et al. HFGCN: Hybrid Filter Graph Convolutional Network for Heterophilic Graphs. In: International Conference on Intelligent Computing. Singapore: Springer Nature Singapore, 2024. p. 439-450.

Developing Real-Time Scheduling Policy by Deep Reinforcement Learning

BO, Zitong, et al. Developing real-time scheduling policy by deep reinforcement learning. In: 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS). IEEE, 2021. p. 131-142.