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Jiaqi Shao

Federated Learning, Distributed Edge AI, Privacy-Preserving Machine Learning.

Education

Hong Kong University of Science and Technology (2023 -)
Doctor of Philosophy (PhD) in Electronic and Computer Engineering

My superviors: Prof. Bing Luo (DKU) and Prof. Xuanyu Cao (HKUST)

The Chinese University of Hong Kong, Shenzhen (2019 — 2023)
Bachelor of Engineering in Electrical and Computer Engineer, Stream: Computer Engineering

Publications

  1. Shao, J., Lin, T., Cao, X., and Luo, B., “Federated Unlearning: a Perspective of Stability and Fairness”, arXiv e-prints, 2024. doi:10.48550/arXiv.2402.01276.
  2. Shao, J., Han, S., He, C., and Luo, B., "Privacy-Preserving Federated Heavy Hitter Analytics for Non-IID Data", in Workshop on Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities, in Conjunction with ICML 2023 (FL-ICML' 23), Jul. 2023.

Projects

FedKit: Enabling Cross-Platform Federated Learning for Android and iOS

  • We present FEDKIT, which pipelines Cross-Platform FL for Android and iOS development by enabling model conversion, hardware-accelerated training, and cross-platform model aggregation.
  • Our workflow supports flexible federated learning operations (FLOps) in production, facilitating continuous model delivery and training.
  • This is a collaborative project with my supervisor Prof. Luo, DKU undergraduate students Sichang He (lead), Beilong Tang, and Boyan Zhang, as well as collaborators Xiaomin Ouyang (UCLA) and Daniel Nata (Flower).
  • Our work has been ACCEPTED at IEEE INFOCOM 2024 Demo 🎉.
FedKit Model FedKit
FedKit Pipeline Overview FedKit Simulation

FedCampus: A Privacy-Preserving Data Platform for Smart Campus

  • We’re excited to announce the launch of the FedCampus Project - a privacy-preserving smart campus application, available on Android and iOS. 🎉 Video online available.
  • This app implements two key privacy-preserving technologies: Federated Learning and Differential Privacy. Check out our 100 customized smart watches for participants at DKU and FedCampus APP.
  • This is a collaborative project with my supervisor Prof. Luo and DKU undergraduate students.
FedCampus

Edge-based Cross-device Federated Learning Prototypes

  • Our prototype supports Mobile and IoT devices operating at WiFi and USRP-based 4G/5G wireless networks.
  • This is a collaborative project with my supervisor Prof. Luo and students from CUHKSZ
sys iot

Teaching Assistant

  • ELEC3120 - Computer Communication Networks (HKUST, Spring 2024)

Patents

  • B. Luo, J. Shao, Method and Apparatus for Online Parameter Selection in Minimizing the Total Cost of Federated Learning, CN202310485067.8, Apr. 2023, field
  • B. Luo, J. Shao, Method and Apparatus for Online Client Sampling in Minimizing the Training time of Federated Learning, CN 202310484383.3, Apr. 2023, field
  • B. Luo, J. Shao, J. Huang, Method and Apparatus for Frequent Items Mining Using Federated Analytics, CN202310365167.7, Mar. 2023, field
  • B. Luo, J. Shao, J. Huang, Method and Apparatus for Frequent Data Mining Based on Hierarchical Federated Analytics, CN202310330791.3, Mar. 2023, field