← Leaderboards
Yanjie Fu
Missouri University Of Science And Technology
$2,610,627
Attributed
$3,083,171
Total exposure
10
Grants
10
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 $945.6K · FY2018–24$1M$750K$500K$250K$0
'18
'19
'20
'21
'22
'23
'24
Funding mix
By agency
NSF$3,083,171 · 10
By mechanism
—$3,083,171 · 10
Top collaborators
- Wei Zhang2 shared
Grant awards (10)
Collaborative Research: III: Small: Advancing Data-Centric AI through Generative Approaches for Feature Space Reconstruction$400,000
· FY2024 · CSE · contact PI
Collaborative Research: SHF: Small: Decentralized Edge Computing Platform for Privacy-Preserving Mobile Crowdsensing$90,645
· FY2024 · CSE · contact PI
CAREER: Reinforced Imitative Graph Learning: Bridging the Gap between Perception and Prescription in Graph Sequences$500,539
· FY2023 · CSE · contact PI
III: Small: Deep Interactive Reinforcement Learning for Self-optimizing Feature Selection$445,104
· FY2023 · CSE · contact PI
III: Small: Deep Interactive Reinforcement Learning for Self-optimizing Feature Selection$499,985
· FY2022 · CSE · contact PI
CAREER: Reinforced Imitative Graph Learning: Bridging the Gap between Perception and Prescription in Graph Sequences$569,333
· FY2021 · CSE · contact PI
Collaborative Research: SHF: Small: Decentralized Edge Computing Platform for Privacy-Preserving Mobile Crowdsensing$147,875
· FY2020 · CSE · contact PI
EAGER: Collaborative Research: Substructure-aware Spatiotemporal Representation Learning$91,000
· FY2020 · CSE · contact PI
CRII: III: Understanding Urban Vibrancy: A Geographical Learning Approach Employing Big Crowd-Sourced Geo-Tagged Data$164,175
· FY2019 · CSE · contact PI
CRII: III: Understanding Urban Vibrancy: A Geographical Learning Approach Employing Big Crowd-Sourced Geo-Tagged Data$174,515
· FY2018 · CSE · contact PI