Li Shen

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Professor of Informatics

University of Pennsylvania

United States

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About

Li Shen is a Professor of Informatics at the University of Pennsylvania, USA. His research focuses on personalized brain-computer interfaces, genetic analysis in relation to brain structure, and the application of large language models to public health issues. Recent work includes studies on dementia prediction, multi-modal diagnosis of Alzheimer's Disease, and advanced mediation analysis techniques in neuroscience.

Recent Grants

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Translational big data analytic approaches to advance drug repurposing for Alzheimer's disease

Open Date: 2021-05-01

Close Date: 2026-04-30

Grant: Close

Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease Biobanks

Open Date: 2020-09-15

Close Date: 2025-08-31

Grant: Close

Informatics Algorithms for Genomic Analysis of Brain Imaging Data

Open Date: 2020-07-01

Close Date: 2024-03-31

Grant: Close

BIGDATA: IA: Collaborative Research: Asynchronous Distributed Machine Learning Framework for Multi-Site Collaborative Brain Big Data Mining

Open Date: 2019-01-01

Close Date: 2022-12-31

Grant: Close

SCH: INT: Mining Drug-Drug Interaction Induced Adverse Effects from Health Record Databases

Open Date: 2016-09-01

Close Date: 2020-08-31

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Collaborators (13)

Haoyang Wang

Teaching Assistant

University of Texas at Austin

UNITED STATES

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Selena Wang

Assistant Professor

Indiana University School of Medicine

UNITED STATES

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Richard Nowakowski

Professor and Chair

Florida State University

UNITED STATES

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Andrew Saykin

Professor and Director, Center for Neuroimaging and Indiana Alzheimer's Disease Research Center

Indiana University School of Medicine

UNITED STATES

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Mansu Kim

Assistant Professor

Gwangju Institute of Science and Technology

SOUTH KOREA

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Diego Machado Reyes

Rensselaer Polytechnic Institute

UNITED STATES

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Juergen Hahn

Professor

Rensselaer Polytechnic Institute

UNITED STATES

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Hua Wang

Professor

Colorado School of Mines

UNITED STATES

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Matthew Nayor

Boston University School of Medicine

UNITED STATES

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Qi Long

Professor

University of Pennsylvania

UNITED STATES

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Lifang He

Assistant Professor

Lehigh University

UNITED STATES

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CHANGGEE CHANG

Assistant Professor

Indiana University School of Medicine

UNITED STATES

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Mary Regina Boland

Assistant Professor

University of Pennsylvania

UNITED STATES

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Li Shen

Research Interests

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About

Recent Grants

Articles (26)

Subject-adaptive meta-learning for personalized BCI: A fusion of resting-state EEG signal and task-specific information

Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling

S‐GMAS: Genome‐Wide Mediation Analysis With Brain Subcortical Shape Mediators

MG-TCCA: Tensor Canonical Correlation Analysis Across Multiple Groups

SDoH-GPT: using large language models to extract social determinants of health

Predicting explainable dementia types with LLM-aided feature engineering

High-dimensional mediation analysis reveals the mediating role of physical activity patterns in genetic pathways leading to AD-like brain atrophy.

Multi-Modal Diagnosis of Alzheimer’s Disease using Interpretable Graph Convolutional Networks

Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors

Identifying Progression-Specific Alzheimer’s Subtypes Using Multimodal Transformer

Distance-weighted Sinkhorn loss for Alzheimer’s disease classification

Homological Landscape of Human Brain Functional Sub-Circuits

Sex modifies effects of imaging and CSF biomarkers on cognitive and functional outcomes: a study of Alzheimer's disease

Repurposing FDA-Approved Drugs Against Potential Drug Targets Involved in Brain Inflammation Contributing to Alzheimer’s Disease

QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics

Genome-Wide Association Analysis across Endophenotypes in Alzheimer’s Disease: Main Effects and Disease Stage-Specific Interactions

Identifying Alzheimer’s genes via brain transcriptome mapping

Identifying genetic markers enriched by brain imaging endophenotypes in Alzheimer’s disease

Integrative analysis of summary data from GWAS and eQTL studies implicates genes differentially expressed in Alzheimer’s disease

Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment

Identifying genes associated with brain volumetric differences through tissue specific transcriptomic inference from GWAS summary data

Mining High-Level Imaging Genetic Associations via Clustering AD Candidate Variants with Similar Brain Association Patterns

Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions

Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop

Identify Consistent Cross-Modality Imaging Genetic Patterns via Discriminant Sparse Canonical Correlation Analysis

A structural enriched functional network: An application to predict brain cognitive performance

Collaborators (13)

Haoyang Wang

Selena Wang

Richard Nowakowski

Andrew Saykin

Mansu Kim

Diego Machado Reyes

Juergen Hahn

Hua Wang

Matthew Nayor

Qi Long

Lifang He

CHANGGEE CHANG

Mary Regina Boland

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