Author

Gordon Keller

University of California, Santa CruzORCID 0000-0002-0798-6728Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Gordon Keller1 paper · University Health Network

Biology Disciplines

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Bioengineering· 2

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Organism:non-human primate· 2 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Assay:electrophysiology· 1 Assay:imaging· 1

Frequent Co-Authors

Alexie BarbeeiD· 2 shared Celeste Franco· 2 shared Cristian Hernandez· 2 shared Fan LuiD· 2 shared Houpu LiiD· 2 shared Hsin‐ya YangiD· 2 shared Kaelan Schorger· 2 shared Koushik Devarajan· 2 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioengineering

Alexie BarbeeORCID

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2 papers

Recent·Most cited

Development of a wireless bioelectronic actuator for wound healing in a porcine model

Prabhat Baniya, Maryam Tebyani, Wan Shen Hee, Houpu Li, Narges Asefifeyzabadi, Kaelan Schorger, Hsin‐ya Yang, Anthony Gallegos, Kan Zhu, Fan Lu, Gordon Keller, Celeste Franco, Koushik Devarajan, Alexie Barbee, Cristian Hernandez, , Mircea Teodorescu

This paper develops a wireless bioelectronic actuator for wound healing in pigs, showing reduced M1/M2 macrophage ratio and increased re-epithelialization in treated wounds.

Scientific Reports · Nov 7, 2025Peer-reviewedBioengineering

Design and Validation of a Wearable Imaging System for Automated Wound Monitoring in Porcine Model

Wan Shen Hee, Maryam Tebyani, Prabhat Baniya, Celeste Franco, Gordon Keller, Fan Lu, Houpu Li, Narges Asefifeyzabadi, Hsin‐ya Yang, Guillermo Villa-Martinez, Kaelan Schorger, Koushik Devarajan, Alexie Barbee, Cristian Hernandez, Tiffany Nguyen, , Mircea Teodorescu

The paper presents a wearable imaging system for automated wound monitoring in pigs, validated to capture and analyze wound progression using machine learning.

bioRxiv · Dec 18, 2024 · PreprintBioengineering