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Su-In Lee
University Of Washington
$9,377,565
Attributed
$10,042,579
Total exposure
11
Grants
8
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 $2.7M · 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$10,042,579 · 11
By mechanism
R01$3,803,549 · 2
R35$1,943,750 · 1
RF1$1,761,543 · 1
R21$1,618,323 · 4
P30$915,414 · 3
Top collaborators
- Suman Jayadev2 shared
- Bala Gopakumaran Nair2 shared
- Monica Shanta Vavilala2 shared
- Jessica Elaine Young2 shared
Most similar at University Of Washington
Same institution · by research overlap
- Idan Shalev$4,047,201
- Peter S Rabinovitch$49,936,459
- Jessica Elaine Young$10,314,278
- Monica L Oxford$8,493,336
- Carrie Dow-Smith$367,052
Others in their field
Top investigators on “Alzheimer&Apos”
- Jose A Luchsinger · Columbia University Health Sciences$56,595,040
- Eric M Reiman · Banner Health$48,982,487
- Yadong Huang · J. David Gladstone Institutes$40,311,515
- Lindsay A. Farrer · Boston University Medical Campus$34,189,802
- David M Holtzman · Washington University$28,985,806
- Michael W Weiner · Northern California Institute Res &Educ$28,197,224
Research focus
Alzheimer&AposPhenotypeGenesData SetExperimental StudyMolecularHigh DimensionalityLearningComplexBig DataMachine LearningTrainingPathologyMultiomic DataDeep LearningGene ExpressionInnovationBiomedical ResearchTherapeutic TargetBiologicalInterestS DiseaseLinear ModelsMethodology
Grant awards (27)
XAI-TRUST: Explainable AI Techniques to Rigorously Understand, Scrutinize, and Trust Clinical AI$445,848
R01 · FY2025 · EB · contact PI
Core F EXPLAINABLE ARTIFICIAL INTELLIGENCE FOR AGING$336,452
P30 · FY2025 · AG · contact PI
Illuminating early microglial dysfunction in Alzheimer's disease through integration of explainable AI and iPSC models$230,642
R21 · FY2025 · AG
Mapping the landscape of the aged human brain for neurodegenerative disease models$210,861
R21 · FY2025 · AG
IDEAL-XAI: Advancing Explainable AI to Identify Early Driver Events of Alzheimer's Disease$1,761,543
RF1 · FY2024 · AG · contact PI
XAI-TRUST: Explainable AI Techniques to Rigorously Understand, Scrutinize, and Trust Clinical AI$447,621
R01 · FY2024 · EB · contact PI
Mapping the landscape of the aged human brain for neurodegenerative disease models$205,619
R21 · FY2024 · AG
Illuminating early microglial dysfunction in Alzheimer's disease through integration of explainable AI and iPSC models$191,891
R21 · FY2024 · AG
Core F: Artificial Intelligence and Bioinformatics$114,832
P30 · FY2024 · AG · contact PI
Interpretable Machine Learning to Identify Alzheimer's Disease Therapeutic Targets$582,016
R01 · FY2023 · AG · contact PI
Core F: Artificial Intelligence and Bioinformatics$115,646
P30 · FY2023 · AG · contact PI
Interpretable Machine Learning to Identify Alzheimer's Disease Therapeutic Targets$582,016
R01 · FY2022 · AG · contact PI
Opening the Black Box of Machine Learning Models$388,750
R35 · FY2022 · GM · contact PI
Core F: Artificial Intelligence and Bioinformatics$115,313
P30 · FY2022 · AG · contact PI
Interpretable Machine Learning to Identify Alzheimer's Disease Therapeutic Targets$582,016
R01 · FY2021 · AG · contact PI
Opening the Black Box of Machine Learning Models$388,750
R35 · FY2021 · GM · contact PI
Core F: Artificial Intelligence and Bioinformatics$116,103
P30 · FY2021 · AG · contact PI
Interpretable Machine Learning to Identify Alzheimer's Disease Therapeutic Targets$582,016
R01 · FY2020 · AG · contact PI
Opening the Black Box of Machine Learning Models$388,750
R35 · FY2020 · GM · contact PI
Core F: Artificial Intelligence and Bioinformatics$117,068
P30 · FY2020 · AG · contact PI
Interpretable Machine Learning to Identify Alzheimer's Disease Therapeutic Targets$582,016
R01 · FY2019 · AG · contact PI
Opening the Black Box of Machine Learning Models$388,750
R35 · FY2019 · GM · contact PI
Application of Data Sciences in Traumatic Brain Injury$166,620
R21 · FY2019 · LM
Opening the Black Box of Machine Learning Models$388,750
R35 · FY2018 · GM · contact PI
Application of Data Sciences in Traumatic Brain Injury$201,642
R21 · FY2018 · LM
A machine learning approach to identify Alzheimer's disease therapeutic targets$182,187
R21 · FY2016 · AG · contact PI
A machine learning approach to identify Alzheimer's disease therapeutic targets$228,861
R21 · FY2015 · AG · contact PI