Bridging the gap between high-fidelity AI training data and robust application security. I ensure AI models are fed quality intelligence and that the software they run on is impenetrable.
Specializing in creating the "Ground Truth" for ML models. I focus on high-precision labeling and validation to eliminate bias and improve model accuracy.
I create repeatable audit workflows, validate annotation quality, and translate human feedback into safer AI behavior.
Securing the infrastructure where AI lives. I build tools and implement processes to detect vulnerabilities before they reach production.
I automate security checks, map attack paths, and integrate scanning into pipelines so risks are caught before deployment.
Targeted software security projects that demonstrate vulnerability detection, secure tooling, and operational resilience.
Nmap integration with MITRE ATT&CK mapping for proactive threat discovery.
View Project →Regex-driven security event detection and alerting for operational visibility.
View Project →Entropy-based password strength scoring and secure generator validation.
View Project →