Author

Gaurav Sharma

United States Air Force Research Laboratory

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

Same name, identified by ORCID

Biology Disciplines

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Neuroscience· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Approach:mixed model· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Bernard Marius ’t HartiD· 1 shared Brent T. Miller· 1 shared Brianna Croucher· 1 shared Denise Y. P. HenriquesiD· 1 shared Hayley FooiD· 1 shared James A. D’amouriD· 1 shared Jean‐Jacques Orban de XivryiD· 1 shared Mireille E. BrouckeiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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1 shared paperNeuroscience

Bernard Marius ’t HartORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Structure-Guided Biochemical Design of DNA Tweezers As A Dual Target of the Primary Glioblastoma Biomarkers S100A4 and Midkine

Hayley Foo, Gaurav Sharma

This study designs DNA tweezers that selectively bind S100A4 and midkine, biomarkers of glioblastoma invasiveness, using computational methods and molecular docking.

bioRxiv · Apr 29, 2026 · PreprintBioinformatics

Modeling Human Visuomotor Adaptation with a DisturbanceObserver Framework

Gaurav Sharma, Bernard Marius ’t Hart, Jean‐Jacques Orban de Xivry, Denise Y. P. Henriques, Mireille E. Broucke

This paper proposes a disturbance observer framework to model visuomotor adaptation by integrating internal model principles and feedforward learning systems.

PLoS Computational Biology · Feb 4, 2026Peer-reviewedNeuroscience

Physiological detection of flow states across varied gameplay workloads

James A. D’amour, Reeshav Shrestha, Brent T. Miller, Brianna Croucher, Gaurav Sharma, R. Andy McKinley

This study uses physiological data and machine learning to predict flow states during varied gameplay tasks, correlating with self-reported flow experiences.

bioRxiv · Jan 9, 2026 · PreprintNeuroscience