Author

Ameya Kulkarni

Duke University

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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Bioengineering· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:protein sequence· 2 Research Focus:sequence-to-function modeling· 2 Research Focus:protein design· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Kensuke NakamuraiD· 2 shared Nathaniel BlalockiD· 2 shared Philip A. RomeroiD· 2 shared Agrim Babbar· 1 shared Jeonghyeon KimiD· 1 shared Sarah A. FahlbergiD· 1 shared Srinath Seshadri· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 18 mutual co-author links

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2 shared papersBioengineering

Kensuke NakamuraORCID

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2 papers

Recent·Most cited

Functional alignment of protein language models via reinforcement learning

Nathaniel Blalock, Srinath Seshadri, Kensuke Nakamura, Agrim Babbar, Sarah A. Fahlberg, Ameya Kulkarni, Philip A. Romero

This paper introduces RLXF, a framework that aligns protein language models with experimental functional goals, improving the generation of high-functioning protein variants.

Nature Communications · Sep 12, 2026Peer-reviewedBioengineering

Explicit representation of germline and non-germline residues improves antibody language modeling

Jeonghyeon Kim, Nathaniel Blalock, Ameya Kulkarni, Kensuke Nakamura, Philip A. Romero

PRISM improves antibody language modeling by distinguishing germline and non-germline residues, achieving better binding affinity correlation and controllable generation.

bioRxiv · May 11, 2026 · PreprintImmunology