I am a Ph.D. Candidate in Department of Computer Science at Johns Hopkins University, where I'm honored to be advised by Dr. Yinzhi Cao. I'm also working closely with Dr. Neil Gong from Duke University. Before that, I received my M.S. in Security Informatics at Johns Hopkins University and my B.E. in Software Engineer at Shandong University.
My research focuses on the intersection of security, privacy, machine learning (ML), and artificial intelligence (AI). My goal is to develop functional, trustworthy solutions for ML and AI systems.
Currently, my work involves diagnosing, correcting, and steering AI behavior—addressing models that generate unsafe content, including sexually explicit, violent, or sensitive data, ensuring seamless real-world deployment aligned with societal values. I am also working on improving the functionality of privacy-preserving ML, such as accurate federated learning and differential privacy. My work has been featured in media outlets like MIT Technology Review and IEEE Spectrum.
yc [dot] yang [at] jhu [dot] edu  / 
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GitHub  / 
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I am on the job market for tenure-track faculty or postdoctoral positions.
News
11/2024, I gave an invited talk on zero-shot video anomaly detection at Voxel51.
10/2024, I gave an invited talk on Trustworthy AI at Monash University.
09/2024, Our paper on knowledge editing in LLMs has been accepted by EMNLP 2024.
07/2024, Our paper on video anomaly detection using LLMs has been accepted by ECCV 2024.
05/2024, Our paper on mitigating unsafe generation from text-to-image models has been accepted by CCS 2024.
11/2023, Our paper on jailbreaking text-to-image models has been accepted by S&P 2024.
Publications
Conference Papers
2024
SneakyPrompt: Jailbreaking Text-to-image Generative Models Yuchen Yang, Bo Hui, Haolin Yuan, Neil Gong, Yinzhi Cao
In the Proceedings of the IEEE Symposium on Security and Privacy (S&P), 2024
Reported by MIT Technology Review and IEEE Spectrum. paper | slides | code
Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models Yuchen Yang, Kwonjoon Lee, Behzad Dariush, Yinzhi Cao, Shao-Yuan Lo
In the Proceedings of European Conference on Computer Vision (ECCV), 2024
paper | code
SafeGen: Mitigating Sexually Explicit Content Generation in Text-to-Image Models
Xinfeng Li*, Yuchen Yang*, Jiangyi Deng*, Chen Yan, Yanjiao Chen, Xiaoyu Ji, Wenyuan Xu
In the Proceedings of The ACM Conference on Computer and Communications Security (CCS), 2024
(* Co-first Authors)
paper | code
Ripplecot: Amplifying ripple effect of knowledge editing in language models via chain-of-thought in-context learning
Zihao Zhao, Yuchen Yang, Yijiang Li, Yinzhi Cao
In the Findings of Empirical Methods in Natural Language Processing (EMNLP), 2024
The first author finished the paper mainly under my mentoring. paper | code
2023
PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation Yuchen Yang*, Bo Hui*, Haolin Yuan*, Neil Gong, Yinzhi Cao
In the Proceedings of USENIX Security Symposium, 2023
Artifact Badges: Artifacts Available, Artifacts Functional, Results Reproduced. (* Co-first Authors)
paper | code
Fortifying Federated Learning against Membership Inference Attacks via Client-level Input Perturbation Yuchen Yang, Haolin Yuan, Bo Hui, Neil Gong, Yinzhi Cao
In the Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) 2023
paper | code
2022
Addressing Heterogeneity in Federated Learning via Distributional Transformation
Haolin Yuan*, Bo Hui*, Yuchen Yang*, Philippe Burlina, Neil Gong, Yinzhi Cao
In the Proceedings of European Conference on Computer Vision (ECCV), 2022
(* Co-first Authors)
paper | code
2021
Practical Blind Membership Inference Attack via Differential Comparisons
Bo Hui*, Yuchen Yang*, Haolin Yuan*, Philippe Burlina, Neil Gong, Yinzhi Cao
In the Proceedings of Network & Distributed System Security Symposium (NDSS), 2021
(* Co-first Authors)
paper | slides | code
Preprints
Pseudo-Probability Unlearning: Towards Efficient and Privacy-Preserving Machine Unlearning
Zihao Zhao, Yijiang Li, Yuchen Yang, Wenqing Zhang, Nuno Vasconcelos, Yinzhi Cao
paper | code (coming soon)
Experiences
Research Assistant, at Johns Hopkins University, 2020.3 - Present
Research Intern, at Honda Research Institute, 2023.10 - 2024.2