Jiawei Shao

Jiawei Shao

Email: shaojw2@chinatelecom.cn and jiawei.shao@connect.ust.hk

About me

Dr. Jiawei Shao is a Research Scientist at Institute of Artificial Intelligence, China Telecom (TeleAI), Shanghai, under the direction of Prof. Xuelong Li.

He is a Principal Investigator (PI) and leads the AI Flow Group, working on a wide range of topics including multimodal generative models, edge artificial intelligence, and communication network systems. The position paper “AI Flow at the Network Edge” is available at [Preprint].

He received his Ph.D. from the Hong Kong University of Science and Technology in 2024, under the supervision of Prof. Jun Zhang. Before that, he received his B.Eng. from Beijing University of Posts and Telecommunications in 2019.

Openings

There are multiple openings of Researchers/Research Engineers/Interns in the following areas:

  • Vision-language models and multimodal integration
  • Model fine-tuning, compression, and acceleration
  • Device-edge-cloud collaborative inference

If you are interested in joining TeleAI, please send your CV to TeleAI.HR@ChinaTelecom.cn and CC me on the email.

Research interests

  • Edge AI: Device-Edge Cooperative Inference, Neural Data Compression.
  • Generative AI: Multimodal Large Language Models, Gaussian Splatting, Intelligent Agents.
  • Trustworthy AI: Federated Learning, Differential Privacy, Jailbreak Attacks.

News

  • [Nov. 2024] Our paper “AI Flow at the Network Edge” was submitted. [Preprint]
  • [Oct. 2024] Our paper “EVA-Gaussian: 3D Gaussian-based Real-time Human Novel View Synthesis under Diverse Camera Settings” was submitted. [Preprint][Project Page]
  • [Jul. 2024] Our paper “Bidirectional Stereo Image Compression with Cross-Dimensional Entropy Model” was accepted to ECCV 2024. [Paper]
  • [Jun. 2024] Our paper “Graph Neural Network Enhanced Retrieval for Question Answering of LLMs” was submitted. [Preprint]
  • [Jun. 2024] I received the School of Engineering (SENG) PhD Research Excellence Award 2023-24. [E-news article]
  • [Mar. 2024] Our paper “FedCiR: Client-Invariant Representation Learning for Federated Non-IID Features” was accepted to IEEE Transactions on Mobile Computing. [Preprint]
  • [Feb. 2024] Our paper “Feature Matching Data Synthesis for Non-IID Federated Learning” was accepted to IEEE Transactions on Mobile Computing. [Paper]
  • [Dec. 2023] Our paper “Large language models empowered autonomous edge AI for connected intelligence” was accepted to IEEE Communications Magazine. [Paper][微信公众号文章]
  • [Nov. 2023] I am delighted to announce that I have successfully defended my PhD thesis. I would like to sincerely thank Prof. Jun Zhang, Prof. Khaled B. Letaief, Prof. Ross Murch, Prof. Qian Zhang, and Prof. Lin Dai for serving as examiners. Thanks also go to Prof. Hongyu Yu for serving as a chairperson of the examination committee.
  • [Nov. 2023] Our paper “Selective knowledge sharing for privacy-preserving federated distillation without a good teacher” was accepted to Nature Communications. [Paper]
  • [Nov. 2023] Our paper “Defending ChatGPT against Jailbreak attack via self-reminder” was accepted to Nature Machine Intelligence. [Paper]
  • [Nov. 2023] Our paper “Stochastic coded federated learning: Theoretical analysis and incentive mechanism design” was accepted to IEEE Transactions on Wireless Communications. [Paper]
  • [Nov. 2023] I received the HKTIIT Postgraduate Excellence Scholarships in the 2022-23 Academic Year.
  • [Sep. 2023] I presented a poster “EdgeGPT: GPT-empowered autonomous edge inference” on the IEEE Hong Kong 6G Wireless Summit. [Poster]
  • [Sep. 2023] Our paper “Task-oriented communication for edge video analytics” was accepted to IEEE Transactions on Wireless Communications. [Paper][Code]
  • [Jul. 2023] Manuscript “A survey of what to share in federated learning: Perspectives on model utility, privacy leakage, and communication efficiency” was submitted. [Preprint]
  • [Jun. 2023] I received the HKUST RedBird Academic Excellence Award in the 2022-23 Academic Year.

Selected publications (Google Scholar Profile)

  • Edge AI, task-oriented communication:
    • J. Shao, X. Zhang, and J. Zhang, “Task-oriented communication for edge video analytics,” IEEE Trans. Wireless Commun., to appear. [Paper][Code]
    • J. Shao, Y. Mao, and J. Zhang, “Task-oriented communication for multi-device cooperative edge inference,” IEEE Trans. Wireless Commun., vol. 11, no. 1, pp. 73-87, Jan. 2023. [Paper][Code]
    • J. Shao, Y. Mao, and J. Zhang, “Learning task-oriented communication for edge inference: An information bottleneck approach,” IEEE J. Select. Areas Commun, vol. 40, no. 1, pp. 197-211, Jan. 2022. [Paper][Code]
    • J. Shao, J. Zhang, “Communication-computation trade-off in resource-constrained edge inference,” IEEE Commun. Mag., vol. 58, no. 12, pp. 20–26, Dec. 2020. [Paper][Code]
  • Federated learning:
    • J. Shao, F. Wu, and J. Zhang, “Selective knowledge sharing for privacy-preserving federated distillation without a good teacher,” Nature Communications, to appear. [Preprint][Code]
    • J. Shao, Y. Sun, S. Li, and J. Zhang, “DReS-FL: Dropout-resilient secure federated learning for non-IID clients via secret data sharing,” Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), New Orleans, LA, USA, Nov. 2022. [Paper]
  • Generative models and large language models:
    • Y. Shen, J. Shao, X. Zhang, Z. Lin, H. Pan, D. Li, J. Zhang, and K. Letaief, “Large language models empowered autonomous edge AI for connected intelligence,” IEEE Commun. Mag., to appear. [Preprint]
    • Y. Xie, J. Yi, J. Shao, J. Curl, L. Lyu, Q. Chen, X. Xie, F. Wu, “Defending ChatGPT against Jailbreak attack via self-reminder,” Nature Machine Intelligence, pp. 1-11, Dec. 2023. [Paper]

Submitted

  • J. Shao*, Z. Li*, W. Sun*, T. Zhou, Y. Sun, L. Liu, Z. Lin, and J. Zhang, “A Survey of What to Share in Federated Learning: perspectives on model utility, privacy leakage, and communication efficiency,” submitted. [Preprint] (*equal contribution with Zijian Li and Wenqiang Sun)
  • Z. Li, Q. Guo, J. Shao, L. Song, J. Bian, J. Zhang, R. Wang, “Graph Neural Network Enhanced Retrieval for Question Answering of LLMs,” submitted. [Preprint]

  • Y. Hu, Z. Liu, J. Shao, Z. Lin, J. Zhang, “EVA-Gaussian: 3D Gaussian-Based Real-time Human Novel View Synthesis Under Diverse Camera Settings,” submitted. [Preprint][Project Page]

  • J. Shao, X. Li, “AI Flow at the Network Edge,” submitted. [Preprint]