Trustworthy AI
Safety and robustness for large reasoning models, including conflict-driven attack analysis and agentic workflow generation benchmarks.
AI Ph.D. Student
I study trustworthy AI, agentic AI, and computational neuroscience.
Research
Safety and robustness for large reasoning models, including conflict-driven attack analysis and agentic workflow generation benchmarks.
Entity-based encrypted synthetic data for continual pretraining while protecting personally identifiable information.
EEG and fMRI workflows for multi-talker speech analysis from brain activity.
Selected Publications
View allConflicts Make Large Reasoning Models Vulnerable to Attacks. ACL Findings.
Continual Pretraining on Encrypted Synthetic Data for Privacy-Preserving LLMs. EACL findings.
A Survey on LLM-as-a-Judge. The Innovation.
Current
I am supervised by Prof. Lionel Ni and currently work as a research intern at the International Digital Economy Academy in Shenzhen. Previously, I completed an MPhil in Data Science and Analytics at HKUST supervised by Prof. Qiong Luo and a BEng in Computer Science at Wuhan University of Technology.