YUCHEN
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Yuchen Yang

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  /  Google Scholar  /  GitHub  /  CV

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

  • Teaching Assistant, at Johns Hopkins University, 2020.9 - 2020.12, 2022.9 - 2022.12

  • Research Assistant, at Chinese Academy of Sciences, 2018.6 - 2018.9

  • Services

    Conference/Journal Reviewing

  • Program Committee
    • The ACM Conference on Computer and Communications Security (CCS), 2025
    • ACM Workshop on Adaptive and Autonomous Cyber Defense (AACD), 2024

  • Reviewer
    • International Conference of Learning Representations (ICLR), 2025
    • IEEE Transactions on Dependable and Secure Computing (TDSC), 2023/2024
    • IEEE Transactions on Information Forensics & Security (T-IFS), 2024

  • Artifact Evaluation Committee
    • IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2024

  • External Reviewer
    • IEEE Symposium on Security and Privacy (S&P), 2025
    • ACM ASIA Conference on Computer and Communications Security (ASIACCS), 2024
    • USENIX Security Symposium, 2023/2024
    • The ACM Conference on Computer and Communications Security (CCS), 2022
    • IEEE Computer Security Foundations Symposium (CSF), 2022/2024
    • IEEE International Conference on Distributed Computing Systems (ICDCS), 2022

    Organizing and Chairing

  • Session Chair
    • IEEE Workshop on Deep Learning Security and Privacy (DLSP), 2024
  • Miscellaneous

    Meet my two incredibly charming family members!
    Go-Wha, the playful cat

    Go-Wha

    Name Meaning: Pronunciation translates to "Puppy" in Chinese

    Breed: Singapura

    Characteristics: Playful, curious, and always the happiest as a puppy!

    Mao-Dan, the fluffy cat

    Mao-Dan

    Name Meaning: Pronunciation translates to "Snowball" in Chinese

    Breed: Domestic short hair

    Characteristics: As soft and fluffy as freshly fallen snow!

    What's more? How about a cheer leader (former), an off-roading adventurer (recent), and a hotpot lover (forever)!

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