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About

Jiaoyang Li is a leading researcher in multi-agent systems and autonomous robotics, with a primary focus on Multi-Agent Path Finding (MAPF) — the challenge of coordinating collision-free movement for large teams of robots. Her work spans foundational theory, algorithmic innovation, and real-world deployment, making her one of the most influential voices in this rapidly growing field. Li's most celebrated contributions include establishing comprehensive definitions, variants, and benchmarks for MAPF (276 citations), providing the research community with a common framework that has shaped subsequent work across the discipline. Her development of EECBS, a bounded-suboptimal search algorithm for MAPF (186 citations), dramatically improved computational efficiency, making large-scale robot coordination viable for time-sensitive applications like Amazon-style automated warehouses. She has also advanced lifelong and pickup-and-delivery variants of MAPF, addressing the continuous task assignment challenges faced by real-world robotic fleets. More recently, Li has pushed boundaries by integrating kinodynamic constraints through Bézier curve optimization and exploring warehouse layout co-design alongside path planning. Her 2023 League of Robot Runners competition-winning approach further demonstrates her ability to translate theoretical advances into practical, scalable solutions. With hundreds of citations accumulated in just a few years, Li's work is shaping the future of multi-robot coordination.