What I'm working toward
I build the measurement layer for high-stakes decisions, whether the decision is made by a human, a model, or an AI agent.
Agent-based models that simulate how controls actually behave over time — degradation, interaction, cascade failure — calibrated against empirical loss data. Control effectiveness frameworks taken from taxonomy to working simulation. Survival analysis applied to vulnerability lifecycles.
Validation frameworks for LLM-generated decisions, grounded in psychometrics and measurement theory. Model risk validation tooling for cyber risk quantification under emerging regulatory requirements. The question should always be whether the output is correct enough to act on, and how you would know if it is.
I am interested in the work that comes after an organization has decided to be genuinely data-driven about security or AI and discovered that the hard part is building the quantitative infrastructure to support it.
Organizations building quantitative security or AI governance capability — whether that means risk quantification, model validation, or LLM evaluation.
Senior or advisory roles where I can build measurement infrastructure for security and AI decisions inside a company that wants to lead, not follow.
Research collaboration on control effectiveness, loss modeling, AI validation, or the intersection of simulation and security.
If that sounds like your organization or your work:
Reach out on LinkedIn →Laura Voicu
I specialize in cyber risk quantification, AI security, and applied data science: the kind of work where statistical modeling, machine learning, and domain expertise converge to make hard problems measurable. Bayesian inference, Monte Carlo simulation, survival analysis, causal reasoning are some of the tools I use to translate security problems into defensible decisions.
Two decades in technology: data architecture at Credit Suisse, enterprise data architecture and AI/RPA automation, cyber security at Swisscom (where I introduced FAIR risk quantification in 2018), and building Elastic's security data science and security assurance practice, security data warehouse, and leading the cyber risk quantification program. Earlier: research in distributed systems at ETH Zürich and Penn State.
PhD Computer Science (University of Basel) · MSc Physics · CAS Applied Data Science & ML (EPFL) · CISSP
ERQI — Co-Founder & CDSO
FAIR Institute — Standards Committee & Former DACH Co-Chair
Cloud Security Alliance — Lead Author & WG Co-Chair
Global Council for Responsible AI — Former Global Ambassador
Startup Advisory — Product Development & Data/AI Strategy
Denny Wan FAIR Ambassador Europe Award, 2025
Open to advisory, senior roles, research collaboration, or speaking engagements. If you're building something ambitious in quantitative security, AI governance, or measurement infrastructure for high-stakes decisions, I'd like to hear about it.