Author

Kyle A. O’Connell

Deloitte (United States)ORCID 0000-0002-0464-9259Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:benchmark study· 2 Research Focus:benchmarking· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Assay:imaging· 1 Organism:non-human primate· 1 Approach:statistical model· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Collin J. LobbiD· 1 shared Dina Mikdadi· 1 shared Haley T. Engelken· 1 shared Josh J. Catana· 1 shared Juergen A. KlenkiD· 1 shared Laura M. GorrelliD· 1 shared Ross A. Campbell· 1 shared Thad B. Carlson· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

Collin J. LobbORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

ClaroAI-Bench: Evaluating Agentic Scientific Reproducibility on Real Biomedical Papers

Kyle A. O’Connell

ClaroAI-Bench evaluates AI agents' ability to reproduce computational findings from biomedical papers by testing data findability, accessibility, code availability, environment reconstructability, and results reproducibility.

bioRxiv · May 12, 2026 · PreprintBioinformatics

Signal Versus Noise: Evaluating iNaturalist Photos as a Source of Quantitative Phenotypic Data in Plethodon Salamanders using Autoresearch and Agentic AI

Kyle A. O’Connell

This study evaluates the reliability of iNaturalist photos for phenotyping Plethodon salamanders, finding weak geographic signals in continuous traits but stronger results for discrete traits using classifiers.

bioRxiv · Mar 27, 2026 · PreprintEcology

Accelerating genomic workflows using NVIDIA Parabricks

Kyle A. O’Connell, Zelaikha B. Yosufzai, Ross A. Campbell, Collin J. Lobb, Haley T. Engelken, Laura M. Gorrell, Thad B. Carlson, Josh J. Catana, Dina Mikdadi, Vivien R. Bonazzi, Juergen A. Klenk

This study benchmarks NVIDIA Parabricks, a GPU-accelerated software suite, showing significant speedups for germline variant calling and cost savings on cloud platforms.

bioRxiv · Jul 20, 2022 · PreprintBioinformatics