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AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
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B2B teams
Product, research, platform, or compliance teams with real rollout pressure.
Recommended: Quick Audit or Deep Report
Budget signal: Usually several-thousand-dollar review budgets or a clear internal decision owner.
B2P operators
Founders, AI leads, and technical operators who need a sharp first answer before wider spend.
Recommended: Diagnostic Session
Budget signal: Usually a low four-figure entry budget with real expansion potential.
Selective individual
Independent researchers or solo operators with a specific high-value technical question.
Recommended: Diagnostic Session
Budget signal: Should still justify a paid diagnostic rather than free exploration.
Project Topics
Stanford. Princeton. A bioRxiv Paper. So Why Did Nobody Ask Where the Data Goes?
BioClaw processes EHR data. Its primary showcase channel is WhatsApp. We audited the repository: 60/100, Tier 2 Caution. Here is what the bioRxiv paper says that the README does not.
From Repo Scanner to Audit Architecture: What Changed in STEM BIO-AI Through v1.7.8
A technical look at how STEM BIO-AI v1.7.8 became less Python-shaped, more semantically stable, and more inspectable across real audit output surfaces.
Beyond Repo Scanning: How AIRI Expanded the Risk Vocabulary in STEM BIO-AI 1.7.x
How STEM BIO-AI uses the MIT AI Risk Repository as a governed local risk-vocabulary layer without replacing deterministic repository scanning
How Do You Trust the AI Auditor? STEM-AI v1.1.2 and Memory-Contracted Bio-AI Audits
STEM-AI v1.1.2 binds a bio/medical AI repository audit to a machine-checkable memory contract, then demonstrates it on a real open-source bioinformatics repository.
Bridging the Gap: From AI Slop to Mathematical Governance
A mathematical framework for detecting AI-generated code slop using AST distributions, Jensen-Shannon divergence, and geometric governance gates.
I Audited 10 Open-Source Bio-AI Repos. Most Could Produce Outputs. Few Could Establish Trust.
I audited 10 visible repositories. Most could produce outputs. Very few could establish what those outputs meant.
Bio-AI Repository Audit 2026: A Technical Report on 10 Open-Source Systems
We audited 10 prominent open-source Bio-AI repositories using code inspection and STEM-AI trust scoring. 8 of 10 scored T0: trust not established. Here is what the code actually shows.
How do you know when your entire AI pipeline is wrong — not just one model? (EXP-033)
EXP-033 shows how to validate an entire AI pipeline, not just one model, using five-gate checkpoints, reproducible PASS/BLOCK parity, AlphaGenome on/off testing, and fully traceable governance decisions.
What AI Changed About Research Code — and What It Didn’t
The old bottleneck was writing the code. The new bottleneck is proving that the code still means what the theory meant.
What an AI Reasoning Engine Built for Alzheimer's Metabolic Research: A Code Walkthrough
A code walkthrough of an AI reasoning engine for Alzheimer’s metabolic research, showing how literature ingestion, causal inference, and executable biomarker scaffolds generate falsifiable pre-validation hypotheses.
Chaos Engineering for AI: Validating a Fail-Closed Pipeline with Fake Data and Math
A case study in AI governance showing how synthetic invalid inputs, structural disagreement, SIDRCE ethics checks, and end-to-end reliability scoring triggered a safe BLOCK verdict in a biomedical pipeline.
How Failing in 2 Hours Saved 8 Months of Drug R&D: Engineering a "Truthful Null" with Upadacitinib
A bioinformatics case study on Upadacitinib showing how SR9 stability scoring and drift analysis exposed lipid carrier incompatibility early, saving months of drug delivery R&D