Qingqing Ye

Research Interests

My research interests include data privacy and security, and adversarial machine learning. As a practitioner in this field, I am interested in finding and solving real problems in a pragmatic manner. The following are some research fields that I am currently working on.

  • Differential Privacy
    With the prevalence of big data analytics, service providers become increasingly enthusiastic in collecting and analyzing usage data to improve their services. However, the collection of user data comes at the price of privacy risks, not only for users but also for service providers who are vulnerable to internal and external data breaches. As an answer to privacy-preserving data collection and analysis, Differential Privacy, either in its centralized or local setting, has become a de facto standard for individual privacy protection.
  • Adversarial Machine Learning
    With the prevalence of Big Data and AI, machine learning models are trained and deployed to facilitate humans in daily life. However, in many hostile environments, the training and deployment of these models can be undermined and their integrity can be severely jeopardized. Adversarial machine learning studies such security issues and aims for the confidentiality, integrity, availability, and accountability of machine learning techniques under malicious and stressful settings.

Research Grants

  • Efficient OLAP Operations under Local Differential Privacy
    PI: PolyU Research Grant, 2023.05-2026.04, HKD 500,000
  • Byzantine-Robust Data Collection under Local Differential Privacy Model
    PI: Research Grants Council/GRF, 15225921, 2022.01-2024.12, HKD 838,393
  • 恶意敌手模型下的本地化差分隐私技术探索
    PI: National Natural Science Foundation of China (青年科学基金项目), 62102334, 2022.01-2024.12, CNY 300,000
  • Privacy-Preserving Data Analytics under Byzantine Attack
    PI: PolyU Research Grant, 2021.03-2023.06, HKD 250,000
  • Mechanism on Model Privacy Protection
    Co-I: Huawei Technologies Co. Ltd., 2020.10-2023.02, HKD 2,304,600
  • Medical Data Mining based on Belief Rule Base
    PI: National Collegiate Innovation and Entrepreneurship Training Program, 201410386009, 2014.07-2015.06, CNY 20,000

Professional Service

  Journal Reviewer

  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • VLDB Journal (VLDBJ)
  • IEEE Transactions on Dependable and Secure Computing (TDSC)
  • IEEE Transactions on Information Forensics and Security (TIFS)
  • ACM Transactions on Privacy and Security (TOPS)
  • Computers & Security
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • IEEE Transactions on Network and Service Management (TNSM)

  Program Committee Member

  • IEEE International Conference on Data Engineering (ICDE 2022, 2023)
  • AAAI Conference on Artificial Intelligence (AAAI 2023)
  • International Conference on Machine Learning (ICML 2022)
  • International Conference on Database Systems for Advanced Applications (DASFAA 2021, 2022, 2023)
  • The International Workshop on Mobile Ubiquitous Systems and Technologies (MUST 2020)

  Conference Reviewer

  • ACM International Conference on Information and Knowledge Management (CIKM 2020)
  • International Conference on Very Large Databases (VLDB 2019)
  • ACM Conference on Computer and Communications Security (CCS 2019)
  • ACM International Conference on Management of Data (SIGMOD 2017)