Sizhe Chen (陈思哲)

AI Security Researcher

Scholar GitHub LinkedIn X CV Xiaohongshu

Hi! I am a CS Ph.D. candidate at UC Berkeley in Berkeley AI Research (BAIR), working with Prof. David Wagner. I study real-world AI security problems with general and principled solutions. I led the development of StruQ, SecAlign, Meta-SecAlign, and SecOPD, the most robust open LLMs against adaptive prompt injections, the top-1 threat to AI agents. My research has been supported by selective industry fundings, including NVIDIA Graduate Fellowship, Meta FAIR and Google DeepMind through BAIR Commons. I obtained an M.Eng. and a B.Eng. from Shanghai Jiao Tong University.

Securing LLMs Against Prompt Injection for Agentic Applications

Feel free to email me for a talk (abstract and slides) or lecture (slides).

Stanford Security Lunch2026

IBM Research Lunch Talk2026

UC Berkeley NLP Group Seminar2026

UC Berkeley Computer Security Guest Lecture2026

Shanghai AI Lab Xinghe Talk2026

PSU Threats and Cybersecurity Guest Lecture2025

UCSD Security and Cryptography Group2025

Cornell-Tech Trustworthy AI Guest Lecture2025

Google DeepMind Adversarial ML Seminar2025

Duke Generative AI Guest Lecture2025

UC Berkeley Security Seminar2024

Hong Kong Baptist University TMLR Young Scientist Seminar2024

Shanghai Jiao Tong University PAMI Group2024