Faculty
Xiao Zhang is a tenure-track faculty at CISPA Helmholtz Center for Information Security. His research covers topics such as adversarial machine learning, statistical machine learning and optimization. He is particularly intersted in understanding the misbehavior of machine learning models against different adversaries and designing robust systems for various machine learning applications. He received his Ph.D. degree in computer science from University of Virginia, advised by Prof. David Evans in 2022. Prior to that, he obtained his M.S. degree from Department of Statistics at University of Virginia and obtained his B.S. degree in Mathematics from Tsinghua University. He is also a member of the European Laboratory for Learning and Intelligent Systems (ELLIS).
Transactions on Machine Learning Research (TMLR) Generating Less Certain Adversarial Examples Improves Robust Generalization
NeurIPS-Workshop (NeurIPS-W)
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
ICML-Workshop (ICMLW)
ICML-Workshop (ICML-W)
Do Parameters Reveal More than Loss for Membership Inference?
ICML-Workshop (ICML-W)
Understanding Adversarially Robust Generalization via Weight-Curvature Index
IEEE Transactions on Information Forensics and Security Stealthy Targeted Backdoor Attacks Against Image Captioning
Conference on Neural Information Processing Systems (NeurIPS)
Transactions of Machine Learning Research (TMLR)
ICML-Workshop (ICMLW)
Provably Robust Cost-Sensitive Learning via Randomized Smoothing