← Leaderboards
Thomas Pock
New York University School Of Medicine
$813,383
Attributed
$1,845,102
Total exposure
1
Grants
0
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.
Funding over time
peak $498K · FY2018–21$500K$375K$250K$125K$0
'18
'19
'20
'21
Funding mix
By agency
NIH$1,845,102 · 1
By mechanism
R01$1,845,102 · 1
Top collaborators
- Florian Knoll4 shared
- Patricia Margaret Johnson1 shared
- Dana J Lin1 shared
Most similar at New York University School Of Medicine
Same institution · by research overlap
- Ravinder R Regatte$21,435,259
- Ricardo Otazo$7,314,631
- Hersh Chandarana$4,318,399
- Dmitry S Novikov$5,695,763
- Yulin Ge$12,393,958
Others in their field
Other Emerging Leaders on “Acceleration”
- Joel A Lipkin · Four Points Technology, Llc$183,862,844
- Douglas S. Hawkins · Children'S Hosp Of Philadelphia$157,315,120
- Ethan Dmitrovsky · Leidos Biomedical Research, Inc.$96,326,191
- Terry Drinkwine · Carahsoft Technology Corporation$93,741,163
- Mark Marino · Venturewell$61,502,138
- Klaus Romero · Critical Path Institute$58,665,332
Research focus
AccelerationDeep LearningAnatomyAffectAlgorithmsBaseBlindedCharacteristicsAppearanceClinical ImagingAreaClinical TranslationCommunitiesComputer Vision SystemsConditioningConsumptionCostData AcquisitionDatabasesClinical DiagnosisData SetData SpaceClinical ProtocolsDiagnostic
Grant awards (4)
Learning an Optimized Variational Network for Medical Image Reconstruction$436,674
R01 · FY2021 · EB
Learning an Optimized Variational Network for Medical Image Reconstruction$498,014
R01 · FY2020 · EB
Learning an Optimized Variational Network for Medical Image Reconstruction$438,449
R01 · FY2019 · EB
Learning an Optimized Variational Network for Medical Image Reconstruction$471,965
R01 · FY2018 · EB