Engineering Robust Autonomy Under Real-World Constraints

Independent technical advisory in localization, SLAM, and safety-critical AI systems. I focus on structural robustness, certification feasibility, and failure-mode transparency under ISO 26262 and SOTIF.

By the numbers

• 15+ years in safety-critical systems, across automotive, aerospace, and regulated software environments
• 20+ software research and safety projects, including ISO 26262 qualification, SOTIF analysis, and model-based verification programs
• 4 published research papers on semantic constraints and safety-aware AI architectures
• 1 granted European patent (EP 2646316 B1)

Engineering principles that guide my work

Robust autonomy systems are built on explicit assumptions, structural clarity, and measurable failure boundaries, not on optimism or benchmark performance alone.

Determinism. Safety-critical systems require traceability and well-defined state transitions. Where probabilistic components are used, their limits must be explicit and observable.

Structural robustness. Accuracy does not equal stability. I evaluate localization and SLAM systems based on observability limits, ambiguity handling, and real-world degradation behavior.

Certification awareness. ISO 26262 and SOTIF are architectural constraints, not documentation exercises. System design must anticipate auditability, reproducibility, and safety evidence generation from the start.

Strategic insight. Technical depth. Trusted execution.

I help autonomy and AI teams reduce technical uncertainty, expose system-level risks, and prepare complex products for real-world deployment, certification, and investor scrutiny.

Autonomy-specific expertise. Focused on SLAM, perception, localization, system safety, and validation challenges in real-world operating conditions.

Safety and certification mindset. Bridging engineering reality with ISO 26262, SOTIF, safety case preparation, and certification-readiness expectations.

Investor-ready technical clarity. Translating complex architecture, roadmap, and execution risks into clear findings for founders, leadership teams, and private equity stakeholders.

Hands-on technical leadership. Supporting teams not only with assessments, but with practical prioritization, technical direction, and implementation guidance.

From localization theory to certification reality

My work sits at the intersection of autonomy engineering, safety-critical systems, and technical decision-making. With experience across SLAM, perception, localization, and system validation, I help teams understand where autonomy architectures are robust and where hidden risks remain.

Today, I support founders, engineering leaders, and investors with independent technical reviews, certification strategy, and due diligence for autonomy and AI-driven systems.