I develop quantitative models that support complex decision-making in innovation, ethics, and policy. My work integrates theoretical rigor with real-world applicability — from utility functions to stakeholder dynamics.
Complex systems often defy intuition – whether in physical processes, data structures, or decision-making. Turning these into actionable, reproducible models requires deep technical expertise, scientific understanding, and precision in implementation.
To design and build robust, transparent, and purpose-driven models and computational tools that serve as reliable decision bases – from simulation and algorithm development to automated analysis pipelines.
Validated simulation models, custom codebases, and interpretable outputs – enabling smarter research, efficient development processes, and clear communication between teams, stakeholders, and decision-makers.
