Senior Software Engineer & DataOps Lead | OMSCS (AI Track) | CISSP
Applied ML • OSINT/Security Data • Python Automation • Reproducible Systems
Engineer with ~a decade of experience building AI/ML enrichment pipelines and automation for federal security programs. I design reproducible, operationally grounded systems that turn messy real-world data into something models can use — and I publish peer-reviewed research on trustworthy AI and security.
My work sits at the intersection of:
- ML/LLM data enrichment pipelines
- Security & OSINT data analysis
- Python-based automation at scale
- Reproducible, trustworthy system design
- Trustworthy LLM-agent workflows / source attestation — in-progress IEEE work with Prof. Vijay K. Madisetti (Fellow, IEEE)
- CPU side-channel analysis — ICSC 2024
- Insider-threat detection — Springer, 2021
- Provenance & attestation for trustworthy AI-agent workflows
- Reproducible ML/LLM evaluation pipelines
- Applying ML to security and operational datasets
- Digital accessibility in computing (see below)
[keep your three — they're good — but consider promoting the tier-stratified provenance repo if it's public, since it ties to the IEEE work]
- Vice President, National Federation of the Blind — Computer Science Division
- Vice President, National Federation of the Blind — Science & Engineering Division
- Proposing a graduate Digital Accessibility course (OMSCS)
Languages: Python, Bash, SQL ML / Data: Pandas, spaCy, scikit-learn, FastAPI, OpenSearch, Airflow; data enrichment & evaluation pipelines Security: CISSP; OSINT tooling, network labs, defensive infrastructure Tools: Linux • Git • Docker • Cloud