About

Hao Huang, PhD, is a Research Professor of Radiology at the University of Pennsylvania's Perelman School of Medicine and serves as Faculty Director of the Small Animal Imaging Facility at Children's Hospital of Philadelphia. His research focuses on neuroimaging techniques to study brain development, connectivity, and microstructure, with particular interest in neurodevelopmental and psychiatric disorders such as autism and Alzheimer’s disease. Dr. Huang's work involves advanced diffusion MRI, functional MRI, and multimodal approaches to create detailed brain atlases, quantify neural structures, and identify early biomarkers for brain disorders. He is renowned for initiating comprehensive brain mapping studies of developmental human brains during fetal stages, providing unprecedented insights into early brain connectivity, anatomy, and microstructure. His lab aims to develop normative infant brain charts, elucidate the structural and metabolic underpinnings of functional connectivity, and advance neuroimaging biomarkers for early diagnosis and intervention. Dr. Huang is actively involved in NIH-funded projects, contributes to the scientific community through editorial and committee roles, and has made significant contributions to the understanding of brain development and neuroimaging methodologies.

Research topics

• Neuroscience
• Psychology
• Medicine
• Biology
• Computer science

Selected publications

• A layered standards framework for integrating single-cell and spatial omics data into brain cell atlases

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-04

  articleOpen access

  The BRAIN Initiative Cell Atlas Network (BICAN) is generating large-scale multimodal datasets to profile cell types in the human, non-human primate, and mouse brain. The diversity of single-cell and spatial transcriptomic and epigenomic assays, combined with varied experimental contexts, multiple data-generating laboratories and distributed infrastructure, poses substantial challenges for data integration and reuse in BICAN. To address this, we implemented a standards framework that enables layered integration of these data into knowledge-ready products for interoperable brain cell atlases. This framework organizes data based on three progressively structured layers. First, we introduced an assay-agnostic modeling layer that unifies the representation of single-cell and spatial omics data using a common set of biological entities and processes assessed by diverse experimental techniques. Second, we implemented harmonized metadata standards that capture key experimental features linked to biospecimen provenance across heterogeneous tissue sources, species, and preparations, supporting integration and validation while minimizing burden on data contributors. Third, we present an extensible representation for data-driven cell type taxonomies that integrates molecular data with annotations, ontology mappings, and evidence. Together, these contributions represent an end-to-end framework that transforms heterogeneous datasets into structured, interoperable resources that support broad community reuse via mapping algorithms, annotation systems, and visualization platforms. This approach links biospecimen provenance with cell-level outputs and embeds these in a standardized taxonomy format, enabling downstream applications such as cross-dataset integration, reference mapping, and knowledge-driven analysis. More broadly, our work demonstrates a generalizable strategy for enabling an efficient data-to-knowledge pipeline in a large-scale consortium setting.

  PublisherDOI

• Highly replicable multisite patterns of adolescent white matter maturation

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-19

  articleOpen access

  The Adolescent Brain Cognitive Development (ABCD) Study is the largest U.S.-based neuroimaging initiative of adolescent brain maturation. Diffusion MRI (dMRI) provides unique insights into white matter organization, yet applying advanced processing pipelines and managing technical variability across scanning environments remains challenging at scale. To address these issues, we present ABCD-BIDS Community Collection (ABCC) release 3.1.0, including a curated resource of more than 24,000 fully processed ABCD dMRI datasets. ABCC provides fully processed images, nuanced image quality metrics, advanced microstructural measures, and person-specific bundle tractography. Evaluating these rich data revealed that measures of diffusion restriction and non-Gaussianity-in particular the intracellular volume fraction from NODDI and return-to-origin probability from MAP-MRI-were highly sensitive to neurodevelopment and robust to variation in image quality. Additionally, harmonization of microstructural features markedly improved the cross-vendor generalizability of developmental effects. Together, ABCC accelerates reproducible, rigorous research on adolescent white matter development.

  PublisherOA PDFDOI

• TReND: Transformer derived features and regularized NMF for neonatal functional network delineation

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  articleSenior author

  Motivation: Neonatal brain functional organization, characterized by extensive immature networks, remains poorly understood. Few methods were established to accurately parcellate neonate functional networks. Goal(s): We aim to develop novel DL approach to extract reliable features, combined with regularized clustering algorithm for robust neonatal functional network delineation. Approach: We developed a novel computational framework, including transformer-based autoencoder to extract feature from BOLD signals, coupled with regularized NMF clustering algorithm to parcellate simulated and real-world neonatal fMRI. Results: TReND surpasses competing feature extraction techniques like PCA, UMAP, and TD, and outperforms clustering methods: K-PCA, ICA, and NMF, demonstrating high stability and robustness in neonate brain parcellation. Impact: We established TReND, a novel and robust framework, for neonatal functional network delineation. TReND-derived neonatal functional networks could serve as a neonatal functional atlas for perinatal populations in health and disease.

  PublisherDOI

• Machine Learning to Infer Neurocognitive Testing Scores Among Adolescents and Young Adults with Congenital Heart Disease

  Research Square · 2025-06-06

  preprintOpen access
  PublisherOA PDFDOI

• TReND: Transformer Derived Features and Regularized NMF for Neonatal Functional Network Delineation

  Lecture notes in computer science · 2025-09-18 · 1 citations

  book-chapterSenior author
  PublisherDOI

• A one-stop tractography solution for tracing short-range association fibers in early developmental brain

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  articleSenior author

  Motivation: Tracing short-range association fibers (SAFs) in early developmental brains with diffusion-MRI-based tractography is challenging due to smaller brain sizes and less myelination of the white matter (WM) fibers. Few methods can reliably trace SAF in early developmental brain. Goal(s): To reproducibly trace high-fidelity SAFs in infant brains and delineate the maturation of SAFs. Approach: We developed a one-stop tractography solution to reproducibly trace SAFs from infants and young adults through a robust Docker-containerized protocol with cutting-edge short-range tractography algorithm. Results: Heterogeneous SAF clusters in infant and young adult brains were reproducibly reconstructed and their developmental trends were revealed. Impact: The cutting-edge short-range tractography protocol offers important insights into the superficial WM maturation in the early developmental brain. The one-stop cross-platform tool can be used for broader neuroscientific and clinical discoveries on brain development.

  PublisherDOI

• Maturation of long- and short-range tracts in macaque brain with ultra-high-resolution diffusion MRI

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  articleSenior author

  Motivation: Despite paramount neuroscientific significance of macaque brain model, comprehensive delineation of both long- and short-range tracs of developing macaque brain is not available. Goal(s): To reveal long- and short-range white matter (WM) tract maturation with cutting-edge tractography using first-of-their-kinds ultra-high-resolution diffusion MRI (dMRI) datasets of developing macaque brains. Approach: We acquired ultra-high resolution dMRI of neonate, early childhood, and adult macaque brains and traced deep and superficial white matter tracts through advanced dMRI-based tractography. Results: Comprehensive long- and short-range WM tracts were delineated, characterized by differential microstructural changes across all tracts. Impact: The revealed maturational processes of the developmental macaque brain WM tracts, specifically the short-range WM tracts, offer unprecedented insights into common and unique features of brain development across primate species.

  PublisherDOI

• Diffusion MRI Processing in the HEALthy Brain and Child Development Study: Innovations and Applications

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-11-11 · 3 citations

  preprintOpen access

  ABSTRACT The landmark ongoing HEALthy Brain and Cognitive Development (HBCD) study will longitudinally chart brain development in a large sample (projected n =7,200) of infants through age 10 years with multimodal neuroimaging that includes an advanced diffusion MRI (dMRI) acquisition. Here, we detail advances in dMRI image processing developed for HBCD, incorporated into the widely used QSIPrep pipeline. Major changes to preprocessing include improvements in infant brain extraction, distortion correction, and normalization to infant-specific templates. Additionally, we describe a new software package – QSIRecon – that yields rich derived data including diverse maps of tissue microstructure as well as person-specific white matter bundles. Using dMRI data from a subset of the HBCD 1.0 release where age information was available ( n =529 sessions across two time points), we observe critical improvements in data quality with preprocessing and see expected developmental patterns. Moving forward, the publicly-available data from HBCD will rapidly grow to become the largest study of brain development in infancy and early childhood using dMRI. QSIPrep and QSIRecon are openly available and can be applied to other infant and pediatric dMRI datasets.

  PublisherOA PDFDOI

• Abstract 4359776: Adverse Childhood Experiences, Genetic Predisposition, and Lifestyle Factors: Roles in Cardiometabolic-Depression Multimorbidity Trajectories

  Circulation · 2025-11-03

  article1st authorCorresponding

  Background: Adverse Childhood Experiences (ACEs) have profound effects on physical and mental health across the lifespan. However, how ACEs influence the co-occurrence and progression patterns between cardiometabolic diseases (CMDs) and depression remains poorly understood. This study aimed to investigate ACE-related disease progression patterns and evaluate the effect modification of genetic predisposition and lifestyle factors. Method: This study was conducted on a prospective cohort study of 203,449 UK Biobank participants who were free of CMDs and depression at baseline and had complete ACE data. ACEs, including emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect, were assessed, with cumulative ACE scores (range 0-5) categorized as low (0), intermediate (1-2), or high (≥3) exposure. Outcomes included incident CMDs (a composite of type 2 diabetes, coronary artery disease, stroke, and heart failure), depression, their multimorbidity, and mortality. Disease trajectories and transitions were analyzed using multistate models. Both additive and multiplicative interactions of genetic predisposition and healthy lifestyle with ACE exposure were investigated to assess their modification effects. Result: During a median follow-up of 14.8 years, 5859 individuals developed CMD only, 6523 developed depression only, and 1507 developed multimorbidity of CMD and depression. ACE exposure showed dose-response associations with risk of CMD-depression multimorbidity (HRs: 1.07-3.89), with stronger associations observed for depression-related trajectories (HRs: 1.19-3.89) than CMD-related trajectories (HRs: 1.07-3.61). The probability of progressing from depression to multimorbidity (12.8-15.5%) was significantly higher than that from CMD to multimorbidity (4.5-7.2%) across three ACE groups. Emotional abuse showed the strongest associations with depression-related trajectories. High genetic predisposition amplified ACE-associated risks (up to 8.51-fold for the depression-CMD transition), while healthy lifestyle attenuated 30.4-93.2% of the ACE-associated risks. Conclusion: This study underscores the dose-response effect of ACEs on CMD-depression multimorbidity, revealing transition-specific vulnerability to early-life adversity. The findings that genetic predisposition amplifies, while healthy lifestyle attenuates ACE-associated risks, suggest opportunities for targeted intervention strategies.

  PublisherDOI

• Spatiotemporal changes of cortical cytoarchitectural complexity across brain regions and between genders during infancy

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  articleSenior author

  Motivation: Human infancy is characterized by the fastest brain changes. However, little is known about the spatiotemporal dynamics of cortical cytoarchitectural complexity. Goal(s): To reveal spatiotemporal changes of cortical cytoarchitectural complexity across infant brain regions and between genders. Approach: We measured cortical cytoarchitectural maturation during infancy using diffusion kurtosis-derived mean kurtosis maps from multi-shell infant diffusion MRI of the highest resolution available to date and captured both shared and unique cytoarchitectural change patterns employing generalized additive models. Results: The results revealed both common growth trends across brain regions and between genders as well as unique regional and gender differences. Impact: This study offers invaluable insight into spatiotemporal changes in cortical cytoarchitecture by leveraging cutting-edge multi-shell infant diffusion MRI with the highest resolution available to date. The cortical cytoarchitectural trendlines could serve as references for normal infant development and disorders.

  PublisherDOI

Recent grants

• Association of gene expression and brain connectivity in human cerebral cortex development and adulthood

  NIH · $1.8M · 2022–2027

• A Multidisciplinary Center for Developing Human and Non-human Primate Brain Cell Atlases

  NIH · $20.5M · 2022–2027

• Structural Development of Human Fetal Brain

  NIH · $4.6M · 2011–2025

• Infant Atlas of Brain Perfusion

  NIH · $2.4M · 2021–2027

• NIH Grant R21EB009545

  NIH · $451k · 2012

Frequent coauthors

• Minhui Ouyang

  199 shared

• Virendra Mishra

  University of Alabama at Birmingham

  101 shared

• Susumu Mori

  Johns Hopkins University

  96 shared

• Tina Jeon

  Children's Hospital of Philadelphia

  83 shared

• Qinmu Peng

  64 shared

• Yun Peng

  Beijing Children’s Hospital

  64 shared

• Hanzhang Lu

  Johns Hopkins University

  60 shared

• Peter C.M. van Zijl

  Johns Hopkins University

  54 shared

Labs

• Hao Huang LabPI

Awards & honors

• NIH funding support for brain mapping studies
• Editorial Board of Neuroimage
• Committee member of NIH-sponsored BrainSpan Consortium
• Ad Hoc member of NIH Study Sections