I'm a fifth-year Ph.D. candidate at the Institute for AI Industry Research (AIR), Tsinghua University, advised by Prof. Yunxin Liu and working closely with Prof. Ting Cao. I received my B.E. in Electronic Engineering from Tsinghua University in 2022.
I work on on-device AI and embodied AI, with a current focus on efficient deployment of embodied foundation models (VLAs and WAMs) and self-evolving physical intelligence. Homepage · RedNote
Lead work
- Cosmos Lite: Efficient inference for Cosmos 3 robot policies, from on-device serving to parallel simulation rollout.
- OxyGen: Unified KV cache management for multi-task VLA inference.
- Vec-LUT (MobiSys 2026 Best Paper Award Runner-Up): Parallel ultra-low-bit LLM inference on edge devices.
- FlexNN (MobiCom 2024): Memory-adaptive DNN inference on edge devices.
Collaborations
- Zeva: In-context causal learning for generalizable embodied manipulation.
- Zetta ζ (668 stars): A closed-loop embodied harness for self-evolving physical intelligence.
- Embodied.cpp (154 stars): Portable inference for embodied AI models on heterogeneous robots.


