Li Wang

Associate Professor

University of North Carolina at Chapel Hill

United States

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Li Wang is an Associate Professor at the University of North Carolina at Chapel Hill, USA. His research primarily focuses on brain development, with recent articles emphasizing the functional development of the human cerebellum and the impacts of early life environmental factors on brain structure. He is also involved in the development of advanced imaging techniques and deep learning models to enhance the analysis of magnetic resonance images across various applications.

Articles (17)

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2025

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2024

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2023

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2023

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UNITED STATES

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Jakob Seidlitz

University of Pennsylvania

UNITED STATES

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Hongtu Zhu

University of North Carolina

UNITED STATES

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Kathryn Humphreys

Assistant Professor

Vanderbilt University

UNITED STATES

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Mingxia Liu

University of North Carolina at Chapel Hill

UNITED STATES

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Pew-Thian Yap

Adjunct Professor of Computer Science

University of North Carolina at Chapel Hill

UNITED STATES

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Li Wang

Research Interests

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About

Articles (17)

Learning lifespan brain anatomical correspondence via cortical developmental continuity transfer

STF: A spherical transformer for versatile cortical surfaces applications

Functional development of the human cerebellum from birth to age five

Charting brain functional development from birth to 6 years of age

A lifespan-generalizable skull-stripping model for magnetic resonance images that leverages prior knowledge from brain atlases

Flexible Individualized Developmental Prediction of Infant Cortical Surface Maps via Intensive Triplet Autoencoder

Early life phthalate exposure impacts gray matter and white matter volume in infants and young children

Longitudinally consistent registration and parcellation of cortical surfaces using semi-supervised learning

nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species

An end‐to‐end infant brain parcellation pipeline

RClaNet: An Explainable Alzheimer's Disease Diagnosis Framework by Joint Registration and Classification

PETS-Nets: Joint Pose Estimation and Tissue Segmentation of Fetal Brains Using Anatomy-Guided Networks

A foundation model for enhancing magnetic resonance images and downstream segmentation, registration and diagnostic tasks

Self-supervised learning with application for infant cerebellum segmentation and analysis

Four-dimensional mapping of dynamic longitudinal brain subcortical development and early learning functions in infants

Self-supervised learning with application for infant cerebellum segmentation and analysis

Breast Tumor Segmentation in DCE-MRI With Tumor Sensitive Synthesis

Collaborators (11)

Gang Li

Sheng-Che Hung

Tengfei Li

John Gilmore

Martin Styner

Zhengwang Wu

Jakob Seidlitz

Hongtu Zhu

Kathryn Humphreys

Mingxia Liu

Pew-Thian Yap

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