Li Jing

talks---li-jing

Research Area
  • Privacy-preserving LLMs
  • Algorithmic fairness
  • UTS FEIT PhD Post-Thesis Scholarship, 2022 
  • A*STAR Research Attachment Programme Scholarship, 2022
  • Grant 1: “Efficient Materials Design with Fewer Domain Evaluation,” Early Career Research (ECR). 1 Jul 2023 – 31 Jun 2024.
  • Grant 2: “Combatting Prejudice in AI: A Responsible AI Framework for Continual Fairness Testing, Repair, and Transfer,” Digital Trust Centre (DTC) Research. 1 Dec 2023 – 31Nov 2026.
  • Grant 3: “Privacy²: Fine-Tuning Encapsulated LLMs to Downstream Tasks Without Peeking on Private Data,” National Multi-modal LLM Programme (NMLP) Research. 1 Apr 2025 – 31 Mar 2028.

1. J. Li, Y. Yao, Y. Pan, X. Wang, I. W. Tsang, and X. Fu, “Alpha and Prejudice: Improving α-Sized Worst Case Fairness via Intrinsic Reweighting,” IEEE TNNLS, vol. 36, no. 10, pp. 18005-18019, 2025.

2. X. W, J. Li*, I. W. Tsang, and Y. Ong, “Towards Harmless Rawlsian Fairness Regardless of Demographic Prior,” vol. 37, pp. 80908-80935, Neurips 2024. 

3. J. Li, Y. Pan, Y. Lyu, Y. Yao, Y. Sui, and I. W. Tsang, “Earning Extra Performance from Restrictive Feedbacks,” IEEE TPAMI, vol 45, no, 10, pp. 11753-11765, 2023.

4. J. Li, Y. Pan, and I. W. Tsang, “Taming Overconfident Predictions on Unlabeled Data from Hindsight,” IEEE TNNLS, vol 35, no. 10, pp. 14151-14163, 2023.

5. J. Li, Y. Pan, Y. Sui, and I. W. Tsang, “Secure Metric Learning via Differential Pairwise Privacy,” IEEE TIFS, vol. 15, pp. 3640-3652, 2020.

6. Jing Li, Yuangang Pan, Yulei Sui, and Ivor W. Tsang, “Secure Metric Learning via Differential Pairwise Privacy,” IEEE Transactions on Information Forensics and Security, vol. 15, pp. 3640-3652, 2020.

7. Feiping Nie, Jing Li, and Xuelong Li, “Self-Weighted Multiview Clustering with Multiple Graphs,”  International Joint Conference on Artificial Intelligence, pp. 2564-2570, 2017.

8. Feiping Nie, Jing Li, and Xuelong Li, “Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework for Multiview Clustering and Semi-Supervised Classification,” International Joint Conference on Artificial Intelligence, pp. 1881-1887, 2016.

  • IEEE TNNLS, JAIR, PR reviewer
  • ICML, NeurIPS, ICLR reviewer