Ting Wang

About Me

I am Associate Professor and Empire Innovation Scholar in the Department of Computer Science at Stony Brook University. I conduct research at the intersection of machine learning, privacy and security, and aim to develop safe and trustworthy artificial intelligence (AI) technologies. My recent work focuses on improving AI along three major thrusts:

• Security Assurance – resilient against malicious manipulations
• Privacy Preservation – respectful for individual privacy
• Decision-Making Transparency – interpretable to human perception

Before joining Stony Brook, I was Associate Professor in the College of IST at Penn State. I finished my Ph.D. at Georgia Tech and my undergrad study at Zhejiang University.

Team

I lead the Algorithmic Learning, Privacy, and Security (ALPS) lab, where I am privileged to work alongside a team of exceptional talents, both in the past and present:

Current Members – Tanqiu Jiang, Jiacheng Liang, Yuhui Wang, Rongyi Zhu, Ziyi Yin (co-supervised with Fenglong Ma), Zian Wang

Alumni – Changjiang Li (» Palo Alto Networks) Ren Pang (» Amazon), Tianyu Du (» Zhejiang University), Zhaohan Xi (» Binghamton), Xinyang Zhang (» Amazon), Tinghao Xie (» Princeton), Zheng Zhang (» Northwestern), Ningfei Wang (» Meta), Yujie Ji (» Amazon), Sam Nguyen (» Google), Yifan Huang (» Bloomberg)

Join Us! – We are ALWAYS looking for motivated and bright (under)grad students and postdocs. If you know how to build/hack AI systems, we should talk! Please email me your resume and set up a time to discuss your potential fit to our team.

Recent Publications (Full List)

• Watch the Watchers! On the Security Risks of Robustness-Enhancing Diffusion Models
  Changjiang Li, Ren Pang, Bochuan Cao, Jinghui Chen, Fenglong Ma, Shouling Ji, Ting Wang
  USENIX Security Symposium (USENIX’25)

• You Can’t Steal Nothing: Mitigating Prompt Leakages in LLMs via System Vectors
  Bochuan Cao, Yuanpu Cao, Changjiang Li, Yameng Ge, Ting Wang, Jinghui Chen
  ACM Conference on Computer and Communications Security (CCS’25)

• RobustKV: Defending Large Language Models against Jailbreak Attacks via KV Eviction
  Tanqiu Jiang, Zian Wang, Jiacheng Liang, Changjiang Li, Yuhui Wang, Ting Wang
  International Conference on Learning Representations (ICLR’25)

• RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models
  Tanqiu Jiang, Changjiang Li, Fenglong Ma, Ting Wang
  International Conference on Learning Representations (ICLR’25)

• SongBsAb: A Dual Prevention Approach against Singing Voice Conversion based Illegal Song Covers
  Guangke Chen, Yedi Zhang, Fu Song, Ting Wang, Xiaoning Du, Yang Liu
  Network and Distributed System Security Symposium (NDSS’25)

Teaching

Stony Brook

• Computer System Security (Fall 2025)
• Adversarial Machine Learning (Spring 2024, Spring 2025)

Penn State

• CYBER 366: Malware Analytics (Spring 2023, Spring/Fall 2022)
• IST 597: Adversarial Machine Learning (Spring 2020, Spring 2021)
• DS 300: Data Privacy and Security (Fall 2019, Fall 2020)

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