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Jeremias Sulam
Johns Hopkins University
$888,750
Attributed
$888,750
Total exposure
1
Grants
1
Lead (contact PI)
Attributed= this PI's even-split share of every grant they're on (the fair, additive number). Exposure = full size of all those grants. They are the sole PI on all grants (the two match).
Funding over time
peak $318.5K · FY2023–25$500K$375K$250K$125K$0
'23
'24
'25
Funding mix
By agency
NIH$888,750 · 1
By mechanism
R01$888,750 · 1
Top collaborators
No co-investigators on record.
Most similar at Johns Hopkins University
Same institution · by research overlap
- Vu Minh Quan$3,197,952
- Neil A Goldenberg$4,077,863
- John D Groopman$13,586,469
- Zhaoli Sun$13,175,173
- Nirupama Putcha$7,704,235
Others in their field
Other Rising Stars on “Disease Classification”
- Jennifer Lee O'Brien · University Of South Florida$10,506,386
- Cathryn Peltz · Henry Ford Health + Michigan State University Health Sciences$7,977,678
- Christopher J. Lindsell · Vanderbilt University Medical Center$5,384,363
- Emily Rose Pfaff · University Of Colorado Denver$4,409,463
- Richard Austin Moffitt · University Of Colorado Denver$4,409,463
- Matt William Wright · Baylor College Of Medicine$3,905,052
Research focus
Disease ClassificationDisparityDiagnostic ImagingDiagnostic ToolDiagnostic AccuracyAlgorithmsBindingDiagnosisAreaDeep Neural NetworkArtificial IntelligenceCancer ImagingCertificationArtificial Neural NetworkChest ImagingClinically RelevantClinical/RadiologicAnatomyComplexBreast Cancer DetectionBreast ImagingData SetCancer DiagnosisEnsure
Grant awards (3)
SCH: Quantifying and mitigating demographic biases of machine learning in real world radiology$287,564
R01 · FY2025 · CA · contact PI
SCH: Quantifying and mitigating demographic biases of machine learning in real world radiology$282,680
R01 · FY2024 · CA · contact PI
SCH: Quantifying and mitigating demographic biases of machine learning in real world radiology$318,506
R01 · FY2023 · CA · contact PI