PMHNP | Clinical AI workflow automation | Healthcare ops tooling | Human-in-the-loop AI systems

I build practical AI-assisted tools for clinical and operational workflows: intake summarization, care-team routing, follow-up tracking, website prototypes, and safety checklists for using AI in healthcare settings.

My work sits at the intersection of psychiatric practice, product thinking, and hands-on automation. The common thread is simple: AI systems should reduce cognitive load, preserve human judgment, and make the next safe action easier to see.

• Licensed psychiatric clinician building hands-on AI workflow prototypes.
• Comfortable translating messy operational work into structured queues, checks, and review loops.
• Focused on synthetic demos, PHI safety, and responsible human-in-the-loop design.
• Currently building toward medical AI consulting, clinical operations automation, and practical evaluation of AI tools in healthcare environments.

• Runnable Python demos with public unit tests and GitHub Actions checks.
• Synthetic workflow visuals for clinical AI, care coordination, site builds, and consulting review.
• Public safety boundary: synthetic data only, no PHI, no production clinical exports.
• Fast review path: docs/portfolio-walkthrough.md
• Weekly status: docs/portfolio-status.md
• Learning shortlist: docs/repo-learning-shortlist.md

• Clinical workflow automation with synthetic data and human review gates.
• Healthcare operations tooling for follow-up queues, message triage, and documentation support.
• AI-assisted site and app builds for small teams that need fast, usable prototypes.
• Safety patterns for PHI handling, synthetic demo data, prompt evaluation, and clinical escalation.

• Synthetic clinical workflow tools with clearer review gates and better demo polish.
• Care coordination routing patterns that separate operations from clinician review.
• Medical AI consulting artifacts that show decision quality, safety boundaries, and workflow judgment.
• AI-assisted site and app prototypes that feel usable, not just generated.

• clinical-ai-workflow-sandbox
  Synthetic clinical workflow demo for intake summaries, longitudinal snapshots, follow-up queues, and safety checks.

• whatsapp-care-coordination-sandbox
  Synthetic care-team messaging demo for routing operational messages into human-reviewed action queues.

• ai-site-build-showcase
  Case-study gallery of AI-assisted website and app builds, focused on fast iteration and usable interfaces.

• medical-ai-consulting-playbook
  Practical checklists for AI workflow risk review, PHI safety, human-in-the-loop design, and model evaluation.

• bootcamp-learning-archive
  Organized index of older FinTech, ML, cybersecurity, and blockchain coursework retained as learning history.

• I know the clinical workflow from the inside, which helps me spot where AI should support judgment rather than replace it.
• I build small proof-of-concept tools first, then evaluate whether they reduce ambiguity, save time, or create new risk.
• I treat synthetic data, auditability, and escalation rules as product requirements, not afterthoughts.
• I am especially interested in AI systems for healthcare operations, clinician productivity, and candidate/workflow evaluation.

Public repositories use synthetic or generalized examples only. I do not publish patient data, private clinical records, production credentials, private operational exports, or vendor-specific internal workflows.

• Small tools that turn messy work into clear queues.
• Clinical-facing summaries that show uncertainty instead of hiding it.
• AI workflows that keep final responsibility with a human reviewer.
• Lightweight prototypes that prove an idea before a team overbuilds it.

See docs/current-build-roadmap.md for the next set of public upgrades I am actively building across the portfolio.

See docs/weekly-portfolio-maintenance.md for the automated weekly maintenance rules.