At IonSQA, I lead AI governance, clinical software QA, and data integrity consulting for biotech, pharma, and healthcare clients. My work includes regulatory gap analysis and AI-informed validation to support FDA, GxP, and ISO 13485 compliance.
At IMAT Solutions, I led QA review and validation of clinical data pipelines across CCD, FHIR, flat-file, and HL7 formats. I also developed a Python-based automation tool using agentic AI in VS Code to validate XML structures and tags, reducing time to production promotion by 70%.
At Ilum Health Solutions / Infectious Disease Connect, I built and managed the QA department supporting healthcare platforms across web, mobile, and back-end systems. I also performed clinical validation of an AI-powered machine-learning antibiogram, including checks of real-time data ingestion and predictive accuracy.
Earlier, I led QA and validation work across government, healthcare, finance, and software projects, including independent validation for New York State of Health and a Medicaid database migration from IBM Mainframe DB2 to MS SQL. I bring experience in system validation, clinical data quality, regulatory compliance, and AI-supported testing.

