Sergey Plis

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Associate Professor

University of Georgia

United States

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About

Sergey Plis is an Associate Professor at Georgia State University, USA. His research primarily focuses on neuroimaging, with recent articles addressing topics such as interpretable disorder signatures, fMRI signal separation, and privacy-preserving quality control of neuroimaging datasets. His work also encompasses the development of analytical tools and frameworks for advancing artificial intelligence applications in neuroimaging.

Recent Grants

Grant: Close

RI: Small: Collaborative Research: Learning Causal Structure from Complex Time Series Data

Open Date: 2013-09-01

Close Date: 2016-08-31

Articles (14)

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2020

Collaborators (3)

Roger Newman-norlund

University of South Carolina

UNITED STATES

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Anand Sarwate

Associate Professor

Rutgers University

UNITED STATES

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Qasim Zia

Georgia College & State University

UNITED STATES

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Sergey Plis

Research Interests

Explore related searches

Contact this professor

About

Recent Grants

Articles (14)

Interpretable Disorder Signatures: Probing Neural Latent Spaces for Schizophrenia, Alzheimer’s, and Autism Stratification

Using an ordinary differential equation model to separate rest and task signals in fMRI

Scaling Synthetic Brain Data Generation

Explainable Self-Supervised Dynamic Neuroimaging Using Time Reversal

Brainchop: Providing an Edge Ecosystem for Deployment of Neuroimaging Artificial Intelligence Models

HistoJS: Web-Based Analytical Tool for Advancing Multiplexed Images

A simple but tough-to-beat baseline for fMRI time-series classification

Brainchop: In-browser MRI volumetric segmentation and rendering

Statelets: Capturing recurrent transient variations in dynamic functional network connectivity

Privacy‐preserving quality control of neuroimaging datasets in federated environments

A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation

A Deep Learning Model for Data-Driven Discovery of Functional Connectivity

Multidataset Independent Subspace Analysis With Application to Multimodal Fusion

Addressing Inaccurate Nosology in Mental Health: A Multilabel Data Cleansing Approach for Detecting Label Noise From Structural Magnetic Resonance Imaging Data in Mood and Psychosis Disorders

Collaborators (3)

Roger Newman-norlund

Anand Sarwate

Qasim Zia

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