← Leaderboards
Nina De Lacy
University Of Washington
$1,060,906
Attributed
$1,060,906
Total exposure
2
Grants
2
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 $249K · FY2019–23$250K$187.5K$125K$62.5K$0
'19
'20
'21
'22
'23
Funding mix
By agency
NIH$1,060,906 · 2
By mechanism
R00$747,000 · 1
K99$313,906 · 1
Top collaborators
No co-investigators on record.
Most similar at University Of Washington
Same institution · by research overlap
- Adrienne L Fairhall$10,255,125
- Peter Tarczy-Hornoch$19,484,298
- David Charles Atkins$11,777,615
- Sara R. Curran$1,977,637
- John D Storey$11,315,975
Others in their field
Other Emerging Leaders on “Abstracting”
- Dale Sandler · Social And Scientific Systems, Inc.$59,740,435
- Susan M Landau · University Of California Berkeley$47,252,026
- Scott Topper · Broad Institute, Inc.$31,924,684
- Anthony Philippakis · University Of California Santa Cruz$25,715,617
- Yunda Huang · Fred Hutchinson Cancer Center$21,871,570
- Scott Rusk · Boston University Medical Campus$19,172,606
Research focus
Abstracting10 Year OldAdolescenceAdolescentArtificial IntelligenceArtificial Neural NetworkBehaviorBehavioralBig DataBioinformaticsBiologicalBiometryBrainCategoriesCharacteristicsChildClinical Decision-MakingClinically RelevantCloud ComputingCognitiveCommunitiesComplexComputational ScienceData Science
Grant awards (5)
Deep machine learning to delineate trajectories of vulnerability and transition to mental illness in youth$249,000
R00 · FY2023 · MH · contact PI
Deep machine learning to delineate trajectories of vulnerability and transition to mental illness in youth$249,000
R00 · FY2022 · MH · contact PI
Deep machine learning to delineate trajectories of vulnerability and transition to mental illness in youth$249,000
R00 · FY2021 · MH · contact PI
Deep machine learning to delineate trajectories of vulnerability and transition to mental illness in youth$156,897
K99 · FY2020 · MH · contact PI
Deep machine learning to delineate trajectories of vulnerability and transition to mental illness in youth$157,009
K99 · FY2019 · MH · contact PI