I am currently an Assistant Professor of Institute for AI Industry Research (AIR). I received my PhD degree and Bachelor’s degree in Computer Science, both from Peking University. I had also worked as a Visiting PhD Student at Carnegie Mellon University. Before joining AIR, I was a Senior Researcher in the Systems Research Group at Microsoft Research Asia.

My research interest lies in the area of Edge AI Systems/Applications. I’ve published in premier venues of mobile computing, artificial intelligence, and software engineering, including a best paper nomination in UbiComp 2016, a best paper in IS-EUD 2017, and a best paper in GreenCom 2023. Some of the papers have become popular open-source tools (DroidBot, PrivacyStreams, Humanoid, etc.) in the area.

I’m recently enthusiastic about building EdgeLLM (large language models at the edge) and MobileAgent (intelligent personal agents on mobile devices) powered by EdgeLLM. Check out our position & survey paper.

Our team is recruiting PostDocs, research engineers, and interns. Please feel free to contact me if you are interested.

Recent News

• 📢 2024/03 – Our group won the First Prize in AIR Winter Camp 2024. Congrats to winning team members Shanhui Zhao, Hao Wen, Wenjie Du and Cheng Liang!
• 📢 2024/03 – One paper got accepted to ACM MobiSys 2024: “Empowering In-Browser Deep Learning Inference on Edge Through Just-In-Time Kernel Optimization”. Congrats to all collaborators!
• 📢 2024/02 – We are hosting a workshop on edge foundation models (EdgeFM 2024) in Tokyo, Japan, Co-located with MobiSys 2024. Please consider submitting your work and joining us in person!
• 📢 2024/01 – Our position & survey paper on mobile LLM agents “Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security” was released. Feeling excited to work in this new area! [arXiv], [GitHub], [机器之心报道]
• 📢 2023/12 – Our paper “Retrieval-based Battery Degradation Prediction for Battery Energy Storage System Operations” got a Best Paper Award in IEEE GreenCom 2023. Thanks and congratulations to our awesome intern Yixuan Li and partners at GDS!
• More…

Summary of My Research

• Improving Edge AI Efficiency
  • Systems optimization for AI inference/training (MobiSys22, MobiSys23, MobiCom24b, MobiSys24)
  • Efficient model customization for edge (MobiCom23, arxiv)
  • Efficient mobile AI applications (MobiCom21, MobiCom22)
• Enhancing Edge AI Reliability
  • Attacks & defense (FSE20, ICSE21, ICSE22, TOSEM23)
  • Diverse and dynamic data distribution (UbiComp21, ICLR22)
  • Data and model privacy (FSE21, UbiComp21, ISSTA21)
• Building Mobile LLM Agents
  • UI-grounded mobile task automation (ICSE17, ASE19, MobiCom24a)
  • On-device data management & analytics (UbiComp17a, BigData18)
  • Lightweight LLM at the edge (arxiv)