Author

Ankit Vishnubhotla

Columbia UniversityORCID 0009-0009-7387-0027Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Assay:electronic health records· 2 Research Focus:clustering· 1 Approach:contrastive learning· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Cole HurwitziD· 2 shared Liam PaninskiiD· 2 shared Agnès LandemardiD· 1 shared Akash SrivastavaiD· 1 shared Alejandro Pan-VazqueziD· 1 shared Amalia Makri-Cottington· 1 shared Anne E UraiiD· 1 shared Anne K. ChurchlandiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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2 shared papersNeuroscience

Cole HurwitzORCID

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Author profile →

3 papers

Recent·Most cited

NeuroscienceNature CommunicationsPeer-reviewedSep 25, 2026

Combatting nonidentifiability to infer motor cortex inputs yields similar encoding of initial and corrective movements

Peter Malonis, Ankit Vishnubhotla, Nicholas G. Hatsopoulos…·Matthew Tyler Kaufman

The paper infers motor cortex inputs during movement tasks and finds similar encoding for initial and corrective movements despite nonidentifiability challenges.

14 citationstop 1%

mouseelectronic health records

𝕏 PostBluesky

NeuroscienceNature MethodsPeer-reviewedJun 25, 2024

Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools

Dan Biderman, Matthew R Whiteway, Cole Hurwitz…·Liam Paninski

88 citationstop 1%

imagingmachine learning (classical)

𝕏 PostBluesky

NeurosciencebioRxivPreprintOct 30, 2023

Towards robust and generalizable representations of extracellular data using contrastive learning

Ankit Vishnubhotla, Charlotte Loh, Liam Paninski…·Cole Hurwitz

This work introduces a contrastive learning framework for extracellular data, showing improved performance over specialized methods in spike sorting and cell-type classification.

1 citation

electronic health recordscontrastive learning

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