Jose Luis Ambite

Associate Research Professor

University of Southern California

United States

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Dr. Jose Luis Ambite is an Associate Research Professor at the University of Southern California. His research focuses on neuroimaging analysis, deep learning architectures for Alzheimer's disease, and innovations in single-cell transcriptomics. He has contributed to various projects, including federated learning frameworks and tools for enhanced data discovery and usability in neuroimaging. His recent articles explore advanced methodologies for improving the detection and analysis of neurodegenerative conditions.

Articles (12)

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2024

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2021

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2021

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2021

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2021

Collaborators (8)

Donna Niedzwiecki

Duke University

UNITED STATES

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John Darrell Van Horn

Professor

University of Virginia

UNITED STATES

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Satya Sahoo

Associate Professor

Case Western Reserve University

UNITED STATES

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Meredith Franklin

Associate Professor

University of Toronto

CANADA

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Kenan Li

Assistant Professor

Saint Louis University

UNITED STATES

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Larisa Soldatova

Professor in Data science

Goldsmiths University of London

UNITED KINGDOM

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Yue Wang

University of North Carolina at Chapel Hill

UNITED STATES

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Greg Ver Steeg

Associate Professor

University of California, Riverside

UNITED STATES

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Jose Luis Ambite

Research Interests

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About

Articles (12)

q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics

A federated learning architecture for secure and private neuroimaging analysis

Comparison of deep learning architectures for predicting amyloid positivity in Alzheimer’s disease, mild cognitive impairment, and healthy aging, from T1-weighted brain structural MRI

NeuroBridge ontology: computable provenance metadata to give the long tail of neuroimaging data a FAIR chance for secondary use

NeuroBridge: a prototype platform for discovery of the long-tail neuroimaging data

Federated Deep Learning for Detecting Alzheimer’s Disease in Multi-Cohort Brain MRI

Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings

Alzheimer’s Disease Detection with a 3D Convolutional Neural Network using Gray Matter Maps from T1-weighted Brain MRI

BD2K Training Coordinating Center's ERuDIte: The Educational Resource Discovery Index for Data Science

W-TSS: A Wavelet-Based Algorithm for Discovering Time Series Shapelets

Rapid detection of identity-by-descent tracts for mega-scale datasets

NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding

Collaborators (8)

Donna Niedzwiecki

John Darrell Van Horn

Satya Sahoo

Meredith Franklin

Kenan Li

Larisa Soldatova

Yue Wang

Greg Ver Steeg

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