Li Jing
Research Area
- Trustworthy AI
- Fairness, Privacy, and Agentic Safety
- 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. Wu J., Li J., I. Tsang, I. W., & Zhang X. (2026). Plug-and-Adapt: Multimodal Coreference Resolution at First Sight with a Pretrained Alignment Model. IEEE Transactions on Multimedia. Accepted. (Corr. Author)
2. Li, J., Yao, Y., Pan, Y., Wang, X., Tsang, I. W., & Fu, X. (2025). Alpha and prejudice: Improving α-sized worst-case fairness via intrinsic reweighting. IEEE Transactions on Neural Networks and Learning Systems, 36(10), 18005–18019.
3. Wang, X., Li, J., Tsang, I., & Ong, Y. S. (2024). Towards harmless Rawlsian fairness regardless of demographic prior. Advances in Neural Information Processing Systems (NeurIPS), 37, 80908–80935. (Corr. Author)
4. Yao, Y., Pan, Y., Li, J., Tsang, I. W., & Yao, X. (2024). Generative adversarial ranking nets. Journal of Machine Learning Research, 25(119), 1–35.
5. Wang, S., Zhang, X., Li, J., Wei, X., Lau, H. C., Dai, B. T., Huang, B. H., Xiao, Z., & Fu, X. (2024). Fuel-saving route planning with data-driven and learning-based approaches: A systematic solution for harbor tugs. IJCAI. (Corr. Author)
6. Li, J., Pan, Y., Lyu, Y., Yao, Y., Sui, Y., & Tsang, I. W. (2023). Earning extra performance from restrictive feedbacks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(10), 11753-11765.
- Reviewer: ICML, NeurIPS, ICLR, IEEE TPAMI, IEEE TNNLS