I'm a 5th-year Ph.D. candidate at Institute for AI Industry Research (AIR), Tsinghua University, advised by Prof. Yunxin Liu, working closely with Prof. Ting Cao. I received my B.E. in Electronic Engineering from Tsinghua University in 2022. I was at EESAST and NICS-EFC.
My research interest has developed from on-device AI to embodied AI. I currently work on efficient deployment of embodied foundation models (VLAs and WAMs) and self-evolving physical intelligence.
Homepage (news, blog) · Google Scholar · Zhihu 知乎 · Rednote 小红书 (looking forward to 1k followers 😆)
First / co-first:
- OxyGen (NeurIPS 2026): unified KV Cache management for VLA inference under multi-task parallelism
- Cosmos Lite: efficient inference and parallel rollout for Cosmos 3 robot policies on consumer-grade GPUs
- ActProbe: a lightweight action-space probe for early failure detection of robot policies
Collaborations:
- Zetta ζ (1k+ stars🔥): an efficient closed-loop embodied harness for self-evolving physical intelligence
- Zeva: in-context causal learning (ICCL) for generalizable embodied manipulation
- EmbodiSkill (integrated into Microsoft/SkillOpt): a training-free skill-aware framework for self-evolving embodied agents
- Embodied.cpp (100+ stars): a portable inference runtime for embodied AI models on heterogeneous robots
First / co-first:
- Vec-LUT (MobiSys 2026 Best Paper Award Runner-Up🏅): vector table lookup for parallel ultra-low-bit LLM inference
- FlexNN (MobiCom 2024): an adaptive memory management framework for DNN inference under memory constraints
Collaborations:
- Personal LLM Agents (500+ citations🔥): a survey and position paper on personal LLM agents, where I led the Efficiency section
- Time's Up (EMNLP 2025): an empirical study of LLM reasoning ability under strict output length constraint