@hwyler
About
I am a CAIO and Professor of AI Risk & Compliance. My mission is to demystify "Governance" by turning it into an engineering problem.
In a world where most AI leadership is limited to policy papers and slide decks, I build the automated control frameworks that survive regulatory audits. My work focuses on the intersection of predictive risk modeling and AI governance.
My Technical Stack & Focus:
- Predictive Risk: I use Scikit-Learn for systemic risk indices and TensorFlow/PyTorch to deploy risk-detection models in production environments.
- Automated Compliance: I build Python-based pipelines to automate evidence collection, model monitoring, and incident response.
- Governance-as-Code: Transforming ISO 42001, NIST AI RMF, and EU AI Act requirements into executable code and telemetry-driven oversight.
I share the "war stories" of deploying AI at scale, the code that failed, the models that worked, and the Python-based architecture you need to survive a board-level audit. Expect deep dives into risk quantification, model drift, bias mitigation, and how to scale AI governance without slowing down your engineering teams.
Available for
I am available for select speaking engagements, executive workshops, and board-level advisory sessions. I don’t bring canned presentations; I bring battle-tested playbooks, live coding demonstrations, and hard-won lessons from the front lines of global AI deployment. Whether you are an event organizer looking for a high-impact keynote, or a C-Suite team needing a deep-dive into control architecture, I deliver the "how" alongside the "why." My Availability & Engagement Areas Keynotes & Conference Speaking - Zero-Fluff AI Strategy: From PoC-heavy stagnation to production-grade ROI. - The Regulatory Tightrope: Navigating the EU AI Act, ISO 42001, and DORA without killing innovation. - AI War Stories: How to build defensible systems that survive board audits and regulatory scrutiny. Technical Workshops (The "Hands-On" Series) - Governance-as-Code: Building automated compliance pipelines using Python, Scikit-Learn, and TensorFlow. - Risk Quantification: Moving away from "heat maps" to monetary risk modeling (Monte Carlo simulations, bias exposure quantification). - The Defensive IDE: Live walkthroughs of using SHAP and custom Python scripts to audit black-box classifiers. AI, IT and GRC Executive Roundtables - Risk-Adjusted Prioritization: Teaching leadership teams how to kill 40% of their "dead" AI projects and scale the 10% that matter. - Cybersecurity & AI: Hardening AI systems against systemic vulnerabilities and vendor supply chain breaches. - Evidence-of-Effectiveness: Structuring your control environment to be audit-ready on Day 1. Academic & Guest Teaching - IE Law School Perspectives: Exploring the intersection of regulatory design, technical implementation, and legal accountability. - Future-Proofing Curricula: Bridging the gap between law school theory and the realities of modern engineering. Why work with me? I am the practitioner who can talk to your Board about P&L and your Data Science team about model_drift. If your goal is to help your audience or your organization move beyond AI anxiety and into AI accountability, let’s connect. I prioritize engagements where I can provide a tangible "toolbox", code repos, canvases, or frameworks, so that participants leave not just inspired, but equipped. Are you looking to book a speaker who actually builds what they teach? Let’s schedule a brief call to discuss your event's specific objectives.
