Author

Eric Karl Oermann

NYU Langone HealthORCID 0000-0002-1876-5963Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:benchmarking· 1 Assay:imaging· 1 Research Focus:protein design· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Ayaka HachisukaiD· 1 shared Biyu Jade HeiD· 1 shared Daniel J. FriedmaniD· 1 shared Fedor E. PanoviD· 1 shared Ignacio SáeziD· 1 shared Jonathan D. ShoriD· 1 shared Orrin DevinskyiD· 1 shared Patricia C. DuganiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperNeuroscience

Ayaka HachisukaORCID

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2 papers

Recent·Most cited

An interpretable peptide-HLA model emergently learns binding energetics and structure

Sully F. Chen, Robert Steele, Eric Karl Oermann

The paper introduces an interpretable model for predicting peptide-HLA binding that matches state-of-the-art performance using only sequence data.

bioRxiv · Sep 14, 2026 · PreprintBioinformatics

Neural and Computational Mechanisms Underlying One-shot Perceptual Learning in Humans

Ayaka Hachisuka, Jonathan D. Shor, Xujin Chris Liu, Daniel J. Friedman, Patricia C. Dugan, Ignacio Sáez, Fedor E. Panov, Yao Wang, Werner Doyle, Orrin Devinsky, Eric Karl Oermann, Biyu Jade He

This study identifies high-level visual cortex as the neural substrate for one-shot perceptual learning and develops a deep neural network model that replicates human behavior and neural coding.

Nature Communications · Feb 4, 2026Peer-reviewedNeuroscience