Xiaoting Li

Staff Research Scientist

Research areas: Program analysis, adversarial machine learning and graph learning

Xiaoting Li, Visa Research scientist.


Dr. Xiaoting Li joined Visa Research as a Staff Research Scientist in March 2022. Xiaoting received her Ph.D. in Information Sciences and Technology at Penn State University in 2022, and did her bachelor’s in information security from University of Electronic Sciences and Technology of China and University of Strathclyde in 2017. In her Ph.D. dissertation, she focused on studies of enhancing the robustness of different ML systems and exploring the applicability of adversarial machine learning in security-critical scenarios.

As a member of Artificial Intelligence team, her research interests span from Machine Learning/Deep Learning to Software Security and Program Analysis. In particular, she did extensive study on software fuzzing problem and adversarial machine learning among various model types. She has published multiple works in top-tier conferences, including International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), SIAM International Conference on Data Mining (SDM), International Conference on Software Engineering (ICSE), AAAI Conference on Artificial Intelligence, and others.


The Good, the Bad and the Ugly: Exploring the Robustness and Applicability of Adversarial Machine Learning; Xiaoting Li, 2022


  1. Xiaoting Li, Yuhang Wu, Vineeth Rakesh Mohan, Yusan Lin, Hao Yang, Fei Wang, “SMARTQUERY: An Active Learning Framework for Graph Neural Networks through Hybrid Uncertainty Reduction.” The Conference on Information and Knowledge Management (CIKM), 2022
  2. Xiaoting Li, Lingwei Chen, and Dinghao Wu. “Adversary for Social Good: Leveraging Attribute Obfuscating Attack to Protect User Privacy on Social Networks.” The EAI International Conference on Security and Privacy in Communication Networks (SecureComm), 2022. 
  3. Xiaoting Li, Xiao Liu, Lingwei Chen, Rupesh Prajapati, and Dinghao Wu. “ALPHAPROG: reinforcement generation of valid programs for compiler fuzzing.” The Association for the Advancement of Artificial Intelligence Conference (AAAI), 2022.
  4. Xiaoting Li, Lingwei Chen, and Dinghao Wu. “Turning Attacks into Protection: Social Media Privacy Protection Using Adversarial Attacks.” SIAM International Conference on Data Mining (SDM), 2021.
  5. Xiaoting Li, Lingwei Chen, Jingquan Zhang, James Larus, and Dinghao Wu. “Watermarking-based Defense against Adversarial Attacks on Deep Neural Networks.” International Joint Conference on Neural Networks (IJCNN), 2021.