Tyler Smith builds security tools for data pipelines and computational workflows, with a particular interest in regulated environments. He has over 7 years of experience developing machine learning models and data pipelines, and holds Security+.

Tyler develops and maintains pkgaudit, a package-aware static analysis security tool that identifies security-relevant code across the R package lifecycle – addressing an under-appreciated software supply chain risk in regulated analytics environments.

His other security projects span network threat detection, cloud vulnerability management, and AI security, including a network intrusion detection model trained on 2.8 million flows and a serverless vulnerability-enrichment pipeline hardened against prompt injection.

Tyler earned a PhD in epidemiology, where he built reproducible analyses and data pipelines for regulated research. He brings a practitioner’s understanding of data science and analytic workflows, helping him design security controls that protect pipelines without losing sight of their purpose. Earlier in his career, Tyler worked in environmental risk assessment and frequently engaged with federal and state regulatory agencies, including the U.S. Food and Drug Administration.