About Me

I am a third-year PhD student at King's College London, supervised by Prof. Jie M. Zhang, and a visiting student at the Southern University of Science and Technology, where I am supervised by Prof. Yepang Liu. Previously, I earned my MSc from the University of Birmingham with Prof. Edward Tarte and my BEng from Guangzhou University with Prof. Zhijia Zhao. I am committed to advancing trustworthy and reliable AI software and agents. My research interests primarily focus on AI agents, AI ethics, AI4Healthcare, SE4AI.

I am currently on the job market and seeking a postdoctoral position in research related to AI agents, AI alignment, SE4AI and AI4Healthcare.

News

• Mar 2026
  Our paper "Fairness Testing of Large Language Models in Role-Playing" (by Xinyue Li, Zhenpeng Chen, Jie M. Zhang, Ying Xiao, Tianlin Li, Weisong Sun, Yang Liu, Yiling Lou, Xuanzhe Liu) is accepted by FSE 2026.
• Dec 2026
  Our paper "Fairness Is Not Just Ethical: Performance Trade-Off via Data Correlation Tuning to Mitigate Bias in ML Software" (by Ying Xiao, Shangwen Wang, Sicen Liu, Dingyuan Xue, Xian Zhan, Yepang Liu, Jie Zhang) is accepted by ICSE 2026.
• Nov 2024
  Our paper "Mitigating Medical Bias in Large Language Models by Prompt Engineering: An Empirical Study of Effectiveness and Trade-offs" (Ying Xiao, Zhenpeng Chen, and Jie M. Zhang) is accepted by Philosophical Transactions of the Royal Society A.
• Apr 2024
  Our paper "MirrorFair: Fixing Fairness Bugs in Machine Learning Software via Counterfactual Predictions" (by Ying Xiao, Jie M. Zhang, Yepang Liu, Mohammad Reza Mousavi, Sicen Liu, Dingyuan Xue) has been accepted by FSE 2024.

Selected Publications

1. Fairness Testing of Large Language Models in Role-Playing Xinyue Li, Zhenpeng Chen, Jie M. Zhang, Ying Xiao, Tianlin Li, Weisong Sun, Yang Liu, Yiling Lou, Xuanzhe Liu Proceedings of the ACM on Software Engineering (FSE 2026) Core A* CCF-A
2. Fairness Is Not Just Ethical: Performance Trade-Off via Data Correlation Tuning to Mitigate Bias in ML Software Ying Xiao, Shangwen Wang, Sicen Liu, Dingyuan Xue, Xian Zhan, Yepang Liu, and Jie M. Zhang IEEE/ACM 48th International Conference on Software Engineering (ICSE 2026) Core A* CCF-A
3. Mitigating Medical Bias in Large Language Models by Prompt Engineering: An Empirical Study of Effectiveness and Trade-offs Ying Xiao, Zhenpeng Chen, and Jie M. Zhang Philosophical Transactions of the Royal Society A JCR Q1
4. Software Fairness Dilemma: Is Bias Mitigation a Zero-Sum Game? Zhenpeng Chen, Xinyue Li, Jie M. Zhang, Weisong Sun, Ying Xiao, Tianlin Li, Yiling Lou, and Yang Liu Proceedings of the ACM on Software Engineering (FSE 2025) Core A* CCF-A
5. MirrorFair: Fixing Fairness Bugs in Machine Learning Software via Counterfactual Predictions Ying Xiao, Jie M. Zhang, Yepang Liu, Mohammad Reza Mousavi, Sicen Liu, Dingyuan Xue Proceedings of the ACM on Software Engineering (FSE 2024) Core A* CCF-A
6. A Comprehensive Study of Real-World Bugs in Machine Learning Model Optimization Hao Guang, Ying Xiao, Jiaying Li, Yepang Liu, Guangdong Bai IEEE/ACM 45th International Conference on Software Engineering (ICSE 2023) Core A* CCF-A

Preprints

• Bias in Large AI Models for Medicine and Healthcare: Survey and Challenges Ying Xiao, Zhenpeng Chen, Jen-tse Huang, Wenting Chen, Yepang Liu, Kezhi Li, Mohammad Reza Mousavi, Richard Dobson, and Jie M. Zhang
• AMQA: An Adversarial Dataset for Benchmarking Bias of LLMs in Medicine and Healthcare Ying Xiao, Jie Huang, Ruijuan He, Jing Xiao, Mohammad Reza Mousavi, Yepang Liu, Kezhi Li, Zhenpeng Chen, Jie M. Zhang
• FITNESS: A Causal De-correlation Approach for Mitigating Bias in Machine Learning Software Ying Xiao, Shangwen Wang, Sicen Liu, Dingyuan Xue, Xian Zhan, and Yepang Liu

Invited Talks

• 2026
  Mitigating machine learning software bias via correlation tuning

  London, United Kingdom
• 2024
  Mitigating machine learning software bias via ensembling counterfactual predictions

  Porto de Galinhas, Brazil