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About

Sofie Haesaert is a leading researcher in the intersection of formal methods, control theory, and robotics, with a focus on enabling provably correct autonomous systems in complex, uncertain environments. Her work centers on temporal logic planning and control synthesis, where she develops rigorous mathematical frameworks to ensure that robots—from cooperative space exploration teams to autonomous vehicles—behave safely and effectively even under partial information and runtime changes. A key contribution is her pioneering approach to specification-guided active exploration, demonstrated in her most cited work (34 citations), which uses linear temporal logic to direct a copter-rover team in maximizing scientific knowledge during Mars-like missions. She has also advanced modularized control synthesis for complex signal temporal logic specifications, significantly reducing the computational burden of mixed-integer programming for long-horizon tasks. Her research on cautious planning with incremental symbolic perception (6 citations) introduces verified reactive driving maneuvers, bridging the gap between symbolic reasoning and continuous control. More recently, Haesaert has tackled risk-aware model predictive control for stochastic systems with runtime temporal logics (4 citations), addressing the critical challenge of dynamic, changing mission objectives. Her work is distinguished by its rigorous guarantees on satisfaction probabilities and safety, making her a pivotal figure in the quest for trustworthy, autonomous decision-making.