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Hi, my name is
Security Research Engineer | Building Secure Systems at Scale
I build tools that make software more secure. From agentic security pipelines to LLM red-teaming frameworks, I work at the intersection of cybersecurity and AI.
I'm a cybersecurity professional with experience spanning security research, application security, penetration testing, and AI/ML security. I enjoy building tools that automate the hard parts of security — from multi-agent code review systems to adversarial testing frameworks.
Currently, I work as a Security Research Engineer at the University of North Dakota's Center for Cyber Security Research, where I design agentic security pipelines and lead adversary emulation exercises.
I hold an MS in Cybersecurity Analytics & Operations from Penn State. Before moving to research, I spent several years in industry doing penetration testing, threat modeling, and security architecture reviews at companies like Capgemini and Siemens.
Multi-Agent Adversarial Security Review Tool
PyPI package with GitHub Actions integration. Uses 3 AI agents in parallel blind review with an adversarial debate engine for comprehensive code security analysis.
Agentic Pentesting Orchestrator
Meta-agent pentesting orchestrator with headless browser automation, confidence scoring, and 73% accuracy on XBOW benchmarks.
AI-Native Multi-Agent AppSec Scanner
Architecture-aware security scanner combining SAST and DAST agents with support for 11+ programming languages.
Retrieval-Augmented Security Analysis Agent
Python vulnerability analysis agent integrating static analyzers (Bandit, Semgrep) with a RAG layer to produce vulnerability reports and remediation guidelines without model fine-tuning, improving detection accuracy by 35%.
LLM Red-Teaming Framework
Contributed BadCharacters probe using differential evolution and Levenshtein distance optimization for adversarial LLM testing.
05. Contact
I'm always open to discussing security research, new projects, or opportunities. Drop me a line.
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