About me

Welcome to Jinyuan Jia’s homepage!

I am an Assistant Professor of Information Sciences and Technology at the Pennsylvania State University. My current research focuses on 1) identifying security/safety issues of LLM-centered AI systems, and 2) enhancing the trustworthiness (e.g., transparency) of those systems.

Previously, I was a postdoc at the University of Illinois Urbana-Champaign under the supervision of Prof. Bo Li. I received a B.E. from the University of Science and Technology of China (USTC) in 2016, a M.E. from Iowa State University in 2019, and a Ph.D. from the Electrical and Computer Engineering Department at Duke University under the supervision of Prof. Neil Zhenqiang Gong in 2022.

Research Interests

• Provably secure/robust machine learning system
• Security/safety of LLM-centric AI system
• Security and privacy vulnerabilities of other machine learning system (federated learning, foundation model ecosystem, graph neural network, etc.)

Selected Publications (Full List)

• Yanting Wang, Wei Zou, and Jinyuan Jia. “FCert: Provably Robust Few-Shot Classification in the Era of Foundation Model”. In IEEE Symposium on Security and Privacy (IEEE S&P), 2024.

• Zaishuo Xia*, Han Yang*, Binghui Wang, and Jinyuan Jia. “GraphGuard: Provably Robust Graph Classification against Adversarial Attacks ”. In International Conference on Learning Representations (ICLR), 2024. *Equal contribution

• Hengzhi Pei, Jinyuan Jia, Wenbo Guo, Bo Li, and Dawn Song. “TextGuard: Provable Defense against Backdoor Attacks on Text Classification”. In Network and Distributed System Security Symposium (NDSS), 2024.

• Jinyuan Jia*, Yupei Liu*, Yuepeng Hu, and Neil Zhenqiang Gong. “PORE: Provably Robust Recommender Systems against Data Poisoning Attacks”. In USENIX Security Symposium, 2023. *Equal contribution

• Jinyuan Jia*, Yupei Liu*, and Neil Zhenqiang Gong. “BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning”. In IEEE Symposium on Security and Privacy (IEEE S&P), 2022. *Equal contribution

• Jinyuan Jia, Xiaoyu Cao, and Neil Zhenqiang Gong. “Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks”. In AAAI Conference on Artificial Intelligence (AAAI), 2021.

• Minghong Fang*, Xiaoyu Cao*, Jinyuan Jia, and Neil Zhenqiang Gong. “Local Model Poisoning Attacks to Byzantine-Robust Federated Learning”. In USENIX Security Symposium, 2020. *Equal contribution

• Jinyuan Jia, Ahmed Salem, Michael Backes, Yang Zhang, and Neil Zhenqiang Gong. “MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples”. In ACM Conference on Computer and Communications Security (CCS), 2019.

• Jinyuan Jia and Neil Zhenqiang Gong. “AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning”. In USENIX Security Symposium, 2018.

Current Ph.D. Students

• Yanting Wang (08/2023 - Now)
• Wei Zou (08/2023 - Now)