Author

Thomas L. Athey

Johns Hopkins UniversityORCID 0000-0002-8987-3486Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Research Focus:cell type annotation· 2 Assay:electronic health records· 2 Organism:human· 2 Organism:mouse· 2 Approach:benchmark study· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1

Frequent Co-Authors

Brock A. WesteriD· 2 shared Nir ShavitiD· 2 shared Shashata SawmyaiD· 2 shared Abrar Rahman AbiriD· 1 shared Alexander J. RopelewskiiD· 1 shared Ambrose CarriD· 1 shared Anik Kumar SahaiD· 1 shared Anita E. BandrowskiiD· 1 shared

Activity by Year

2022-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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Curved chords = mutual co-authorship

2 shared papersNeuroscience

Brock A. WesterORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

SmartEM: machine-learning guided electron microscopy

Yaron Meirovitch, Ishaan Singh Chandok, Core Francisco Park, Pavel Potocek, Lu Mi, Shashata Sawmya, Yicong Li, Thomas L. Athey, Vladislav Susoy, Neha Karlupia, Yuelong Wu, Daniel Raimund Berger, Richard Lee Schalek, Caitlyn A. Bishop, Daniel Xenes, , Nir Shavit

SmartEM accelerates electron microscopy image acquisition by using machine learning to intelligently allocate imaging time, achieving up to 7-fold speedup in connectomic samples.

Nature Methods · Dec 29, 2025Peer-reviewedNeuroscience

MExConn: A Mechanistically Interpretable Multi-Expert Framework for Multi-Organelle Segmentation in Connectomics

Abrar Rahman Abir, Anik Kumar Saha, Shashata Sawmya, Thomas L. Athey, Nir Shavit, Md. Shamsuzzoha Bayzid

MExConn is a multi-expert U-Net framework for segmenting multiple organelles in EM images, outperforming baselines and offering mechanistic interpretability.

bioRxiv · Nov 19, 2025 · PreprintNeuroscience

The BRAIN Initiative Cell Census Data Ecosystem: A User's Guide

Michael Hawrylycz, Maryann Elizabeth Martone, Patrick R. Hof, Ed S. Lein, Aviv Regev, Giorgio A. Ascoli, Jan Gunnar Bjaalie, Hong‐Wei Dong, Satrajit Ghosh, Jesse A Gillis, Ronna P. Hertzano, David R. Haynor, Yongsoo Kim, Yufeng Liu, Jeremy A. Miller, , Brian Zingg

The paper provides a guide to the BRAIN Initiative Cell Census Network (BICCN) data ecosystem, its tools, and resources for analyzing brain cell types across species.

bioRxiv · Oct 26, 2022 · PreprintBioinformatics