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About

Ani Hsieh is a leading researcher in multi-robot systems, with a focus on developing scalable and theoretically-grounded algorithms for environmental monitoring and cooperative control. Her work bridges robotics, dynamical systems, and fluid mechanics, enabling teams of autonomous vehicles to tackle complex, real-world challenges. A key contribution is her collaborative target tracking framework, which provides performance guarantees for multi-robot coordination (39 citations). She has also pioneered methods for robots to track attracting Lagrangian coherent structures in flows, a breakthrough for energy-optimal path planning in aquatic environments. More recently, Hsieh introduced a distributed, scalable algorithm for non-myopic spatial sampling, allowing robot teams to efficiently collect data from quasi-static fields while accounting for communication constraints. Her editorial work on the *Journal of Field Robotics* special issue on multiple collaborative field robots underscores her leadership in the community. With a career dedicated to pushing the boundaries of autonomy, Hsieh’s research is essential reading for those interested in how robot teams can intelligently explore and understand our dynamic world.