Yorick Sens

Papers

Total Citations

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About

Yorick Sens is a researcher at the forefront of software engineering for artificial intelligence, with a primary focus on the integration and operationalization of machine learning within complex, often safety-critical systems. His work addresses the critical gap between ML model development and robust system deployment, particularly through the identification and formalization of architectural patterns. His most-cited paper, "Towards ML-Integration and Training Patterns for AI-Enabled Systems" (2024), lays foundational groundwork by cataloging reusable solutions for embedding ML components into larger software architectures and automating their complex lifecycles. This contribution is vital for ensuring the reliability and maintainability of AI systems in high-stakes domains. While his citation count is still growing, reflecting the recency of his impactful work, Sens's research is already shaping how practitioners design and build trustworthy AI-enabled software, positioning him as a key voice in the emerging field of AI engineering.