Shiqi Jiang

shijiang AT microsoft.com



profile_pic_2022.jpg

I am a Senior Researcher with Microsoft Research Asia (MSRA). I received the Ph.D. degree in computer science from Nanyang Technological University in 2018, supervised by Prof. Mo Li, and the Bachelor degree from Zhejiang University.

My research interests broadly fall in edge computing, mobile systems and AIoT. My recent research mainly focuses on Edge AI, where I especially investigate the following topics: efficient inference systems on edge devices; LLM-powered agents for edge ecosystems; and AI-powered mobile sensing systems.

I am constantly reruiting research interns. If you are interested in our work, please feel free to contact me.


News

Apr 5, 2025 LUT-Diff was accepcted to TMC. :sparkles::sparkles:
Feb 5, 2025 One paper was conditionally accepcted to SenSys 2025. :sparkles::sparkles:
Oct 27, 2024 One paper was accepcted to TOSEM, one paper as accepected to TMC. 🎊🎊
Mar 9, 2024 One paper was conditionally accepcted to MobiSys 2024. 🎊🎊
Feb 8, 2024 Our measurement study on “In-Browser Deep Learning Inference” was released :tada::tada:

Recent Publications

  1. SenSys ’25
    Babel: A Scalable Pre-trained Model for Multi-Modal Sensing via Expandable Modality Alignment
    Shenghong Dai, Shiqi Jiang, Yifan Yang, Ting Cao, Mo Li, Suman Banerjee, and Lili Qiu
    2025
  2. MobiSys ’24
    Empowering In-Browser Deep Learning Inference on Edge Devices with Just-In-Time Kernel Optimizations
    Fucheng Jia, Shiqi Jiang, Ting Cao, Wei Cui, Xu Cao, Yuanchun Li, Qipeng Wang, Deyun Zhang, Ju Ren, Yunxin Liu, Lili Qiu, and Mao Yang
    2024
  3. MobiCom ’24
    AutoDroid: LLM-powered Task Automation in Android
    Hao Wen, Yuanchun Li, Guohong Liu, Shanhui Zhao, Tao Yu, Toby Jia-Jun Li, Shiqi Jiang, Yunhao Liu, Yaqin Zhang, and Yunxin Liu
    2024
  4. MobiSys ’23
    NN-Stretch: Automatic Neural Network Branching for Parallel Inference on Heterogeneous Multi-Processors
    Jianyu Wei, Ting Cao, Shijie Cao, Shiqi Jiang, Shaowei Fu, Mao Yang, Yanyong Zhang, and Yunxin Liu
    2023
  5. MobiCom ’23
    AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments
    Hao Wen, Yuanchun Li, Zunshuai Zhang, Shiqi Jiang, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, and Yunxin Liu
    2023
  6. SenSys ’22
    Turbo: Opportunistic Enhancement for Edge Video Analytics
    Yan Lu, Shiqi Jiang, Ting Cao, and Yuanchao Shu
    2022
  7. MobiSys ’22
    CoDL: Efficient CPU-GPU Co-Execution for Deep Learning Inference on Mobile Devices
    Fucheng Jia, Deyu Zhang, Ting Cao, Shiqi Jiang, Yunxin Liu, Ju Ren, and Yaoxue Zhang
    2022
  8. MobiCom ’21
    Flexible High-Resolution Object Detection on Edge Devices with Tunable Latency
    Shiqi Jiang, Zhiqi Lin, Yuanchun Li, Yuanchao Shu, and Yunxin Liu
    2021
  9. APSys ’20
    Profiling and Optimizing Deep Learning Inference on Mobile GPUs
    Shiqi Jiang, Lihao Ran, Ting Cao, Yusen Xu, and Yunxin Liu
    2020
  10. IEEE TMC
    Efficient and Adaptive Diffusion Model Inference Through Lookup Table on Mobile Devices
    Qipeng Wang, Shiqi Jiang, Yifan Yang, Ruiqi Liu, Yuanchun Li, Ting Cao, and Xuanzhe Liu
    IEEE Transactions on Mobile Computing Apr 2025
  11. IEEE TMC
    AdaWiFi, Collaborative WiFi Sensing for Cross-Environment Adaptation
    Naiyu Zheng, Yuanchun Li, Shiqi Jiang, Yuanzhe Li, Rongchun Yao, Chuchu Dong, Ting Chen, Yubo Yang, Zhimeng Yin, and Yunxin Liu
    IEEE Transactions on Mobile Computing Oct 2024
  12. ACM TOSEM
    Anatomizing Deep Learning Inference in Web Browsers
    Qipeng Wang, Shiqi Jiang, Zhenpeng Chen, Xu Cao, Yuanchun Li, Aoyu Li, Yun Ma, Ting Cao, and Xuanzhe Liu
    ACM Transactions on Software Engineering and Methodology Aug 2024
  13. ACM TOSN
    Large-Scale Video Analytics with Cloud–Edge Collaborative Continuous Learning
    Ya Nan, Shiqi Jiang, and Mo Li
    ACM Transactions on Sensor Networks Oct 2023