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About

Lasse Beers is a researcher at the intersection of automated production, self-adaptive systems, and model-based systems engineering. His work addresses critical challenges in two seemingly distinct domains: the future of carbon-neutral aviation and the formal verification of reconfigurable software systems. In his most-cited paper, "Challenges in Automated Commercial Aircraft Production" (23 citations), Beers explores how the shift to game-changing technologies like liquid hydrogen propulsion will demand entirely new automated production paradigms. Simultaneously, he has made significant contributions to the formal foundations of self-adaptive systems, developing methods to precompute optimal reconfiguration strategies using stochastic timed game automata and priced timed games. His 2022 and 2024 papers on this topic (4 and 3 citations, respectively) tackle the difficult problem of selecting the best-fitting next configuration under real-time and cost constraints. Most recently, in 2025, Beers has pioneered the integration of AI planning semantics into SysML system models, enabling automated PDDL file generation—a notable achievement that bridges the gap between system modeling and automated planning. His work is particularly valuable for researchers and engineers developing safety-critical, self-adaptive systems that must operate reliably under uncertainty.