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 (Spring/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
  • 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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