Welcome to Pervasive Intelligence Lab 👋

The Pervasive Intelligence Laboratory, directed by Prof. Song Guo, is developing novel and efficient deep learning architectures, algorithms, and systems over ubiquitous mobile, IoT, and wearable devices.

We focus on the following research areas

  • Federated Learning & On-Device Learning
  • Cloud-Edge Hybrid Cyberinfrastructure for Foundation Models
  • Trustworthy AI Governance

Join Us

We are looking for strongly motivated PhD students, Research Assistants, and Postdoctoral Fellows.

Song Guo

We are a family

Latest News

Congratulations to Ziming Liu for his PhD graduation!
Heartfelt congratulations to Dr. Ziming Liu on his PhD graduation! His research has focused on Multi-Label Zero-shot Learning, and he has published papers in multiple top-tier conferences. We’re thrilled to see him embark on his new journey at WXG in Tencent WeChat.
Last updated on Apr 26, 2024 1 min read
Bay Area Youth Science and Technology Talent to the Top of the World, Where is the Road? Special Views Forum was successfully held by CCF HONG KONG

CCF与CCF香港举办《湾区青年科技人才走向国际顶尖，路在何方？》特别观点论坛

Last updated on Dec 14, 2023 1 min read
Prof. Song Guo as one of the world’s most highly cited researchers 2023

Congratulations to Professor Song Guo for being recognised in the list of “Highly Cited Researchers 2023”.

Last updated on Dec 2, 2023 1 min read
Zero Dynamic Medical Technology won Gold Medal at Geneva Inventions Expo

Congratulations to Zhenda Xu and Professor Song Guo for being awarded Gold Medal at the 48th International Exhibition of Inventions Geneva (Geneva Inventions Expo), widely regarded as among the most important annual global events devoted exclusively to inventions.

Last updated on May 4, 2023 1 min read
Prof. Song Guo as one of the world’s most highly cited researchers this year

Congratulations to Professor Song Guo for being recognised in the list of “Highly Cited Researchers 2022”.

Last updated on Nov 22, 2022 1 min read
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Recent Publications

Enyuan Zhou, Song Guo, Zicong Hong, Christian S. Jensen, Yang Xiao, Dalin Zhang, Jinwen Liang, Qingqi Pei (2024). VeriDKG: A Verifiable SPARQL Query Engine for Decentralized Knowledge Graphs. In 50th International Conference on Very Large Data Bases (VLDB) (CCF-A).

Jingcai Guo, Qihua Zhou, Xiaocheng Lu, Ruibin Li, Ziming Liu, Jie Zhang, Bo Han, Junyang Chen, Xin Xie, Song Guo (2024). ParsNets: A Parsimonious Composition of Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning. The 33rd International Joint Conference on Artificial Intelligence (IJCAI)（CCF-A）.

Fushuo Huo, Wenchao Xu, Jingcai Guo, Haozhao Wang, Song Guo (2024). C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation. IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) (CCF-A).

Sikai Bai, Jie Zhang, Song Guo, Shuaicheng Li, Jingcai Guo, Jun Hou, Tao Han, Xiaocheng Lu (2024). DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning. IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) (CCF-A).

Chonghe Zhao, Yipeng Zhou, Shengli Zhang, Taotao Wang, Quan Z. Sheng, Song Guo (2024). DEthna: Accurate Ethereum Network Topology Discovery with Marked Transactions. IEEE International Conference on Computer Communications (INFOCOM) (CCF-A).

See all publications