About

I am a PhD candidate in Computer Science at UMass Amherst, advised by Amir Houmansadr and co-advised by Eugene Bagdasarian.

My research centers on security, privacy, and behavioral properties of AI agent systems. I study how LLM agents interact with tools and connected software, and how that perception-action loop creates new risks such as prompt injection, information leakage, behavioral manipulation, and agent fingerprinting.

My goal is to adapt security thinking for autonomous AI systems: identifying agent-specific vulnerabilities and designing defenses that make agents safer to deploy in real-world environments.


πŸ”¬ Research Interests

  • AI Agent Security – Understanding vulnerabilities specific to AI agents; designing attacks and defenses
  • Web & Browser Agent Security – Dynamic prompt injection, agent observation manipulation, and secure-by-design browser agents
  • Agent Privacy & Attribution – Prompt reconstruction and user profiling from encrypted browsing traces; multi-layer agent fingerprinting
  • LLM Fairness & Behavior – Bias measurement; behavioral drift and persuasion effects in long-running agents
  • Federated Learning & Unlearning – Privacy-preserving algorithms and selective knowledge removal in distributed systems


πŸ“’ Recent News

  • 🧭 Jun 2026 – Started as a Research Intern at Brave Software, studying dynamic prompt injection in browser agents
  • πŸ•΅οΈ Jun 2026 – Released AI Snitches Get Glitches on agentic surveillance evasion
  • 🧬 Jun 2026 – Released Whose Agent Are You? on multi-layer fingerprinting of autonomous web agents
  • 🧠 Feb 2026 – Released Understanding Persuasion in Long-Running Agents
  • πŸ“„ Jan 2026 – Survey on Federated Unlearning accepted to IEEE Big Data 2026
  • πŸ“Š Jan 2026 – Bias similarity across 30 LLMs (Accepted to ICLR 2026)
  • πŸ›‘οΈ Jan 2026 – AI Web and Research Agents (WRAs) (Accepted to USENIX Security 2026)
  • πŸ›‘οΈ May 2025 – Researching vulnerabilities in AI Web and Research Agents (WRAs)
  • 🧩 Mar 2025 – Developing an inference attack on unlearning samples
  • πŸ“Š May 2024 – Analyzed bias similarity across 30 LLMs
  • 🎀 Mar 2024 – Presented research on federated unlearning at NESD 2024
  • πŸ“„ Aug 2023 – Authored a survey paper on federated unlearning systems
  • πŸŽ“ Aug 2023 – Started PhD in Computer Science at UMass Amherst
  • πŸŽ“ Jun 2023 – Completed MS in Computer Science at Sungkyunkwan University