Xuan Wang, Assistant Professor, Electrical and Computer Engineering, College of Engineering and Computing (CEC), will receive funding for the project: “CAREER: A Dynamical Systems Approach to Reliable and Efficient Knowledge Transfer in Robot Learning.”
Wang aims to enable robots to transfer and reuse prior knowledge when encountering new tasks, environments, or hardware platforms. Current robot learning methods often rely on large amounts of data and trial-and-error methods, limiting their use in conditions where data collection is costly, time-consuming, or unsafe.
Drawing on concepts from dynamical systems and control, Wang will study how knowledge transfer occurs, when it breaks down, and how it can be made more efficient.
He holds the resulting advances will support new robot learning approaches that are both effective and data-efficient.
These outcomes align with national priorities by enabling safer, more affordable, and more reliable robotic technologies in areas such as disaster response, healthcare support, environmental monitoring, manufacturing, logistics, and transportation.
Wang is set to receive $639,870 from NSF for this research. Funding will begin in Sept. 2026 and will end in late Aug. 2031.
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