Zitong Bo
薄紫彤
Embodied AI ｜ Large Models ｜ OPC
Focusing on manipulation and loco-manipulation using Vision-Language Models and Vision-Language-Action Models. Seeking self-motivated interns for agentic embodied AI research.
Collaboration / Internship / Investment → bozitong@xiaomi.com
薄紫彤
Zitong Bo
具身智能 ｜ 大模型 ｜ OPC
专注于基于视觉-语言模型（VLM）和视觉-语言-动作模型（VLA）的机械臂操作与移动操作研究。正在寻找有自驱力的实习生，一起做具身智能方向的研究。
合作/实习/投资 ➡️ bozitong@xiaomi.com
Towards Artificial General Intelligence
I received my Ph.D. from the Institute of Software, Chinese Academy of Sciences, where my research covered real-time systems, embedded AI, and reinforcement learning. I was fortunate to be advised by Prof. Ying Qiao at the Human-Computer Interaction Technology and Intelligent Information Processing Laboratory.
I previously worked with Prof. Junliang Xing at the Institute of Automation, CAS. We placed 3rd and 4th in the CIG 2017 and AIIDE 2018 StarCraft AI competitions. I am a Grandmaster-level StarCraft player and passionate about applying AI to games.
- 2025 — Xiaomi Robotics Lab · Senior Algorithm Engineer
- 2018 — 24 ISCAS · Ph.D. in Computer Science
- 2017 — 18 CASIA · Research Intern
- 2014 — 18 USTB · B.S. in Computer Science
迈向通用人工智能
博士毕业于中国科学院软件研究所，研究方向涵盖实时系统、嵌入式 AI 与强化学习，师从乔颖研究员（人机交互技术与智能信息处理实验室）。
曾在中国科学院自动化研究所与邢军亮研究员合作，分别在 CIG 2017 和 AIIDE 2018 星际争霸 AI 竞赛中获得第三名和第四名。星际争霸宗师段位玩家，热衷于将 AI 应用于游戏领域。
- 2025 至今 小米机器人实验室 · 高级算法工程师
- 2018 — 24 中科院软件所 · 博士
- 2017 — 18 中科院自动化所 · 科研实习
- 2014 — 18 北京科技大学 · 本科
Recent Work
近期工作
RTDeepEnsemble: Real-time DNN Ensemble Method for Machine Perception Systems
Designing Real-Time Neural Networks by Efficient Neural Architecture Search
HFGCN: Hybrid Filter Graph Convolutional Network for Heterophilic Graphs
Developing Real-Time Scheduling Policy by Deep Reinforcement Learning
What's Happening
最新消息
Our paper Reinforced Embodied Planning with Verifiable Reward for Real-World Robotic Manipulation is now on arXiv.
I will visit NUS and NTU on September 3–4 to introduce Xiaomi Robotics Lab. We welcome like-minded students to join our team.
9 月 3–4 日将访问新加坡国立大学和南洋理工大学，介绍小米机器人实验室，欢迎志同道合的同学加入。
I officially joined Xiaomi Robotics Lab on January 21, 2025.
2025 年 1 月 21 日正式加入小米机器人实验室。
Our work RTDeepEnsemble accepted at ICCD 2024; oral presentation on November 18 in Milan, Italy.
论文 RTDeepEnsemble 被 ICCD 2024 接收，将于 11 月 18 日在意大利米兰做口头报告。
Our work Developing Real-Time Scheduling Policy by Deep Reinforcement Learning accepted at RTAS 2021 with oral presentation.
论文 Developing Real-Time Scheduling Policy by Deep Reinforcement Learning 被 RTAS 2021 接收并做口头报告。
Get in Touch
Open to collaboration, internship inquiries, and discussions about embodied AI, robotics, and game AI.
欢迎联系
欢迎合作交流、实习咨询，以及关于具身智能、机器人和游戏 AI 的讨论。
Email: bozitong@xiaomi.com · bozitong1996@gmail.com