Dr. Qingqing Ye

Assistant Professor
Department of Electrical and Electronic Engineering
The Hong Kong Polytechnic University
Email: [email protected]

Research Interests
  • Differential privacy
  • Adversarial machine learning

About Me

I received my PhD degree from Renmin University of China in 2020, and joined the Hong Kong Polytechnic University as a Research Assistant Professor since then. In 2022, I was promoted as an Assistant Professor. My research interests include data privacy and security, and adversarial machine learning. You can refer to our research lab ASTAPLE for more information.

I am looking for PhD students (Fall 2025 Admission), Research Assistants, and Postdoctoral Fellows in the field of differential privacy, and adversarial machine learning. If you are interested, please send me your CV at [email protected].

News
  • Nov. 2024: Our paper “Membership Inference Attacks and Defenses in Federated Learning: A Survey” is accepted by ACM Computing Surveys.
  • Nov. 2024: Our paper “Federated Heavy Hitter Analytics with Local Differential Privacy” is accepted by International Conference of Management of Data (SIGMOD 2025).
  • Oct. 2024: Our paper “Generating Location Traces with Semantic-constrained Local Differential Privacy” is accepted by IEEE Transactions on Information Forensics and Security (TIFS).
  • Oct. 2024: Our paper “Boosting Accuracy of Differentially Private Continuous Data Release for Federated Learning” is accepted by IEEE Transactions on Information Forensics and Security (TIFS).
  • Sep. 2024: Our paper “Top-k Discovery under Local Differential Privacy: An Adaptive Sampling Approach” is accepted by IEEE Transactions on Dependable and Secure Computing (TDSC).
  • Jun. 2024: A research project entitled “Harnessing Sensitive Statistics from the Crowd: Towards Scalable Private Federated Analytics” is awarded by Research Grant Council with HK$ 992,994 (2025.01-2027.12).
  • Jun. 2024: Our paper “PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy” is accepted by International Conference on Very Large Databases (VLDB 2024).
  • May 2024: Our paper “RFTrack: Stealthy Location Inference and Tracking Attack on Wi-Fi Devices” is accepted by IEEE Transactions on Information Forensics and Security (TIFS).
  • Mar. 2024: Our paper “Differentially Private Graph Neural Networks for Link Prediction” is accepted by IEEE International Conference on Data Engineering (ICDE 2024).
  • Mar. 2024: Our paper “PrivShape: Extracting Shapes in Time Series under User-Level Local Differential Privacy” is accepted by IEEE International Conference on Data Engineering (ICDE 2024).
  • Mar. 2024: Our paper “Interactive Trimming against Evasive Online Data Manipulation Attacks: A Game-Theoretic Approach” is accepted by IEEE International Conference on Data Engineering (ICDE 2024).
  • Feb. 2024: Our paper “LDPTube: Theoretical Utility Benchmark and Enhancement for LDP Mechanisms in High-dimensional Space” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Feb. 2024: Our paper “A Federated Learning Framework Based on Differentially Private Continuous Data Release” is accepted by IEEE Transactions on Dependable and Secure Computing (TDSC).
  • Jan. 2024: Our paper “LDPGuard: Defenses against Data Poisoning Attacks to Local Differential Privacy Protocols” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Jan. 2024: A research project entitled “Federated Graph Management and Querying: Subgraphs, Keywords, and Privacy” is awarded by Research Grant Council with HK$ 4,854,870 (2024.06-2027.05).

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