🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Max Kerensky

Johns Hopkins University

ORCID: 0009-0008-0138-8218

Also affiliated with Johns Hopkins Medicine

MedicineEngineering

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 7%percentile
0.104Author DataRank

Indexed papers

1in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 1 indexed paper attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

A novel open-source ultrasound dataset with deep learning benchmarks for spinal cord injury localization and anatomical segmentation

Scientific Reports(2025)10.1038/s41598-025-16275-z
Top 78%
0.104DataRank
Top 78%1 citations

Kunal Kotkar, Kelly Jiang, Meghana Bhimreddy, Daniel Davidar, Carly Weber-Levine +14 more

Papers

Driven by 6 papers — median percentile 22. Top paper: “Visualizing tactile feedback: an overview of current technologies with a focus on ultrasound elastography”.

Visualizing tactile feedback: an overview of current technologies with a focus on ultrasound elastography

Frontiers in Medical Technology(2023)10.3389/fmedt.2023.1238129
N/A
0.385DataRank · unranked
12 citations

Kelley M. Kempski Leadingham, Max Kerensky, Sriramana Sankar, Nitish V. Thakor, Amir Manbachi +1 more

A novel open-source ultrasound dataset with deep learning benchmarks for spinal cord injury localization and anatomical segmentation

Scientific Reports(2025)10.1038/s41598-025-16275-z
Top 78%
0.104DataRank
Top 78%1 citations

Kunal Kotkar, Kelly Jiang, Meghana Bhimreddy, Daniel Davidar, Carly Weber-Levine +14 more

A Patient-specific Preplanning Treatment Algorithm for Focused Ultrasound Therapy of Spinal Cord Injury

(2023)10.1109/ner52421.2023.10123718
N/A
0DataRank · unranked
4 citations

Joshua Punnoose, Kelley M. Kempski Leadingham, Max Kerensky, Nicholas Theodore, Nitish V. Thakor +2 more

Quantifying tethered spinal cord tension: Ultrasound elastography results from computational, cadaveric, and intraoperative first-in-human studies

Research Square(2023)10.21203/rs.3.rs-2922525/v1
N/A
0DataRank · unranked
1 citations

Abhijit Paul, Denis Routkevitch, Andrew M. Hersh, Kelley M. Kempski-Leadingham, A. Daniel Davidar +14 more

Tethered spinal cord tension assessed via ultrasound elastography in computational and intraoperative human studies

Communications Medicine(2024)10.1038/s43856-023-00430-6
N/A
0DataRank · unranked
8 citations

Abhijit Paul, Denis Routkevitch, Andrew M. Hersh, Kelley M. Kempski Leadingham, A. Daniel Davidar +14 more

Precision in Spinal Cord Injury Research: A Novel Electromagnetic Impactor for a Consistent Porcine Model

Annals of Biomedical Engineering(2025)10.1007/s10439-025-03836-6
N/A
0DataRank · unranked
0 citations

Abdul Karim Ghaith, Carly Weber-Levine, Kayla Robinson, Christina Krueger, Constantin Smit +15 more