← Leaderboards
Olivier Gevaert
Stanford University
$8,099,347
Attributed
$11,620,978
Total exposure
5
Grants
3
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 $2.5M · FY2015–25$5M$3.8M$2.5M$1.3M$0
'15
'16
'17
'18
'19
'20
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$11,620,978 · 5
By mechanism
R01$5,389,533 · 2
U01$3,767,453 · 1
OT2$2,019,991 · 1
R56$444,001 · 1
Top collaborators
- Calvin J Kuo4 shared
- John B Sunwoo4 shared
- Crystal Mackall2 shared
Most similar at Stanford University
Same institution · by research overlap
- Ronald M Lazar$7,910,610
- Ruijiang Li$10,760,802
- Jia Wu$3,637,726
- Daniel L Rubin$10,989,812
- Pasi A Janne$27,388,753
Others in their field
Top investigators on “Molecular”
- David Heimbrook · Leidos Biomedical Research, Inc.$871,088,761
- Leonard Freedman · Leidos Biomedical Research, Inc.$468,573,385
- Richard Webby · St. Jude Children'S Research Hospital$254,843,170
- Larry Arthur$238,531,074
- Gregory H Reaman · National Childhood Cancer Foundation$230,630,913
- Ralph Parchment · Leidos Biomedical Research, Inc.$193,231,914
Research focus
MolecularTumorMalignant NeoplasmsAlgorithmsGene ExpressionIn VivoPharmaceutical PreparationsDna MethylationImageClinical CareMolecular ProfilingBrain NeoplasmsCancer PatientCohortPredict Clinical OutcomeTechnologyData SetDrug TargetingBaseEpidermal Growth Factor ReceptorBiological MarkersGliomaCancer SiteHigh-Throughput Nucleotide Sequencing
Grant awards (18)
Multimodal AI modeling of T cell therapies to predict patient response and nominate advanced cell design strategies$1,673,650
OT2 · FY2025 · OD
Multi-scale modeling of glioma for the prediction of treatment response, treatment monitoring and treatment allocation$484,000
R01 · FY2025 · CA · contact PI
Multimodal AI modeling of T cell therapies to predict patient response and nominate advanced cell design strategies$346,341
OT2 · FY2025 · OD
Multi-scale modeling of glioma for the prediction of treatment response, treatment monitoring and treatment allocation$515,854
R01 · FY2024 · CA · contact PI
Multi-scale modeling of glioma for the prediction of treatment response, treatment monitoring and treatment allocation$576,312
R01 · FY2023 · CA · contact PI
Multi-scale modeling of glioma for the prediction of treatment response, treatment monitoring and treatment allocation$568,630
R01 · FY2022 · CA · contact PI
Multi-scale modeling of glioma for the prediction of treatment response, treatment monitoring and treatment allocation$363,862
R01 · FY2022 · CA · contact PI
Multi-scale modeling of glioma for the prediction of treatment response, treatment monitoring and treatment allocation$612,041
R01 · FY2021 · CA · contact PI
Radiogenomics framework for non-invasive personalized medicine$444,001
R56 · FY2019 · EB · contact PI
Identification of Cooperative Genetic Alterations in the Pathogenesis of Oral Cancer$924,971
U01 · FY2018 · DE
Radiogenomics Framework for Non-Invasive Personalized Medicine$496,100
R01 · FY2018 · EB · contact PI
Radiogenomics Framework for Non-Invasive Personalized Medicine$255,910
R01 · FY2018 · EB · contact PI
Identification of Cooperative Genetic Alterations in the Pathogenesis of Oral Cancer$924,971
U01 · FY2017 · DE
Radiogenomics Framework for Non-Invasive Personalized Medicine$503,635
R01 · FY2017 · EB · contact PI
Identification of Cooperative Genetic Alterations in the Pathogenesis of Oral Cancer$947,802
U01 · FY2016 · DE
Radiogenomics Framework for Non-Invasive Personalized Medicine$497,664
R01 · FY2016 · EB · contact PI
Identification of Cooperative Genetic Alterations in the Pathogenesis of Oral Cancer$969,709
U01 · FY2015 · DE
Radiogenomics Framework for Non-Invasive Personalized Medicine$515,525
R01 · FY2015 · EB · contact PI