Shengyu Tao
My research interest includes AI-enabled applications for sustainable use of retired electric vehicle batteries (reuse and recycling), e.g., power grid energy storage and critical material recycling. Special attention is paid to state estimation, diagnosis and prognosis under limited and heterogeneous data availability. I also work closely with material scientist on AI for Science (AI4S) topics, such as diagnosis and prognosis of lithium sulfur batteries and lithium metal batteries.
Showing 5 publications
Listening to silent signals: Wireless internal sensing redefines battery safety intelligence
Multi-frequency excitation enables one-second battery diagnostics across life cycle chain
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