Ninghui Li
Computer Science · Purdue University West Lafayette
Publications
298
Citations
17,967
Est. group size
~4
Recurring co-author estimate
Active years
25
Publishing since 2001
Ninghui Li's research focuses on data privacy and security, particularly methods for protecting individual privacy while still allowing useful data analysis, such as differential privacy (a mathematical framework for adding controlled noise to data to prevent identification of individuals) and access control systems that manage who can view or use sensitive data. Recent work also examines privacy risks in large language models, secure electronic voting systems, and privacy-preserving machine learning techniques like federated learning across multiple data sources. This work is relevant to students interested in building systems that balance data utility with formal privacy and security guarantees.
Publication output was relatively steady and higher between 2017-2020 (14-21 papers/year) but has slowed over the last five years, averaging about 6 papers per year with some year-to-year fluctuation.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Fully Transparent, Privacy-Preserving Yet Verifiable, Attack-Resistant, and Practical Remote Electronic Voting Rendering Assured and Fair Elections
IEEE Transactions on Privacy · 2025
- T-Closeness
2025
- Beyond Data Privacy: New Privacy Risks for Large Language Models
arXiv (Cornell University) · 2025
- Differentially Private Vertical Federated Clustering
Proceedings of the VLDB Endowment · 2023
- PolyScope: Multi-Policy Access Control Analysis to Triage Android Scoped Storage
IEEE Transactions on Dependable and Secure Computing · 2023
- PolyScope: Multi-Policy Access Control Analysis to Triage Android Scoped Storage
arXiv (Cornell University) · 2023
- Emigration, Business Dynamics, and Firm Heterogeneity in North Macedonia
IMF Working Paper · 2023
- Augmenting Password Strength Meter Design Using the Elaboration Likelihood Model: Evidence from Randomized Experiments
Information Systems Research · 2022
- Fisher Information as a Utility Metric for Frequency Estimation under Local Differential Privacy
2022
- Differentially Private Data Synthesis: State of the Art and Challenges
Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security · 2022
- Federated matrix factorization with privacy guarantee
Proceedings of the VLDB Endowment · 2021
- PolyScope: Multi-policy access control analysis to compute authorized attack operations in android systems
2021
- Continuous Release of Data Streams under both Centralized and Local Differential Privacy
2021
- T-Closeness
2021
- Improving utility and security of the shuffler-based differential privacy
Proceedings of the VLDB Endowment · 2020
- arXiv (Cornell University)×21
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting×8
- Synthesis lectures on information security, privacy, and trust×5
- Encyclopedia of Database Systems×4
- IEEE Transactions on Dependable and Secure Computing×3
- Zhenhua Chen
Computer Science · The Ohio State University
- Hanshen Xiao
Computer Science · Purdue University West Lafayette
- Wenhai Sun
Computer Science · Purdue University West Lafayette
- Xiaofeng Chen
Computer Science · Purdue University West Lafayette
- Yan Huang
Computer Science · Indiana University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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