Author

Shanglin Li

BIFOLD - Berlin Institute for the Foundations of Learning and Data, Germany

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 1

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Approach:contrastive learning· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:electrophysiology· 1

Frequent Co-Authors

Huu HoangiD· 1 shared Mitsuo KawatoiD· 1 shared Motoaki Kawanabe· 1 shared Okito YamashitaiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

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4 top collaborators · 6 mutual co-author links

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1 shared paperNeuroscience

Huu HoangORCID

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1 paper

Recent·Most cited

Geometry-Conditioned Hyperalignment for Generalizable EEG Decoding Across Datasets and Paradigms

Huu Hoang, Shanglin Li, Okito Yamashita, Motoaki Kawanabe, Mitsuo Kawato

This paper introduces hTSMNet, a method for zero-shot EEG decoding across datasets and paradigms using geometry-conditioned hyperalignment and Riemannian SPD manifold learning.

bioRxiv · Nov 10, 2026 · PreprintNeuroscience