Faculty
2025: AI 2000 Most Influential Scholar Award Honorable Mention 2025
2025: Best Machine Learning and Security Paper in Cybersecurity Award 2025
2022: Busy Beaver Award für "Privacy of Machine Learning"
2021: Busy Beaver teaching award for seminar “Privacy of Machine Learning” at Saarland University (2021 Winter)
2019: Best paper award at NDSS
Dr. Yang Zhang is tenured faculty member at CISPA. His research concentrates on trustworthy machine learning (privacy, safety, and security). Moreover, he works on measuring and understanding misinformation and unsafe content like hateful memes on the Internet. Over the years, he has published multiple papers at top venues in computer science, including CCS, NDSS, Oakland, and USENIX Security. His work has received the NDSS 2019 distinguished paper award and the CCS 2022 best paper award runner-up.
ACM Conference on Computer and Communications Security (CCS) Membership Inference Attacks Against In-Context Learning
ACM Conference on Computer and Communications Security (CCS) SeqMIA: Sequential-Metric Based Membership Inference Attack
Conference on Empirical Methods in Natural Language Processing (EMNLP) Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models
Usenix Security Symposium (USENIX-Security) SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
ACM Conference on Computer and Communications Security (CCS) "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models
Usenix Security Symposium (USENIX-Security) Instruction Backdoor Attacks Against Customized LLMs
Usenix Security Symposium (USENIX-Security) Prompt Stealing Attacks Against Text-to-Image Generation Models
Network and Distributed System Security Symposium (NDSS) Towards Understanding Unsafe Video Generation
Advanced Science Integrating Vision‐Language Models for Accelerated High‐Throughput Nutrition Screening
ACM ASIA Conference on Computer and Communications Security (AsiaCCS) FAKEPCD: Fake Point Cloud Detection via Source Attribution