← Leaderboards
Quanquan Gu
University Of Virginia Main Campus
$5,355,906
Attributed
$6,605,217
Total exposure
15
Grants
12
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 $2.2M · FY2016–24$2.5M$1.9M$1.3M$625K$0
'16
'17
'18
'19
'20
'21
'22
'23
'24
Funding mix
By agency
NSF$6,605,217 · 15
By mechanism
—$6,605,217 · 15
Top collaborators
- Chong Liu2 shared
- David E Evans1 shared
- Hongning Wang1 shared
- Jenny Y Yang1 shared
Grant awards (15)
Collaborative Research: III: Medium: Neural Networks Meet Bandits: Theory, Algorithms and Applications$600,000
· FY2024 · CSE · contact PI
Automated Electrochemical Research based on Deep Learning$900,000
· FY2023 · MPS
CPS: Medium: Collaborative Research: Provably Safe and Robust Multi-Agent Reinforcement Learning with Applications in Urban Air Mobility$399,999
· FY2023 · ENG · contact PI
Collaborative Research: Towards the Foundation of Approximate Sampling-Based Exploration in Sequential Decision Making$300,000
· FY2023 · MPS · contact PI
EAGER: ADAPT: AI-based Categorization to Decipher Reaction Mechanisms from Cyclic Voltammetry$299,999
· FY2021 · MPS
III: Small: Towards the Foundations of Training Deep Neural Networks: New Theory and Algorithms$500,000
· FY2020 · CSE · contact PI
CIF: Small: Collaborative Research: Rank Aggregation with Heterogeneous Information Sources: Efficient Algorithms and Fundamental Limits$250,000
· FY2019 · CSE · contact PI
CAREER: Scaling Up Knowledge Discovery in High-Dimensional Data Via Nonconvex Statistical Optimization$506,020
· FY2018 · CSE · contact PI
BIGDATA: F: Collaborative Research: Taming Big Networks via Embedding$500,000
· FY2018 · CSE · contact PI
BIGDATA: F: Collaborative Research: Taming Big Networks via Embedding$499,879
· FY2018 · CSE · contact PI
III: Small: Collaborative Learning with Incomplete and Noisy Knowledge$350,919
· FY2018 · CSE · contact PI
III: Small: Collaborative Research: High-Dimensional Machine Learning Methods for Personalized Cancer Genomics$300,000
· FY2018 · CSE · contact PI
SaTC: CORE: Small: Multi-Party High-dimensional Machine Learning with Privacy$498,624
· FY2017 · CSE
CAREER: Scaling Up Knowledge Discovery in High-Dimensional Data Via Nonconvex Statistical Optimization$199,777
· FY2017 · CSE · contact PI
III: Small: Collaborative Learning with Incomplete and Noisy Knowledge$500,000
· FY2016 · CSE · contact PI