Yize Zhao, PhD
Associate Professor of BiostatisticsCards
Appointments
Contact Info
About
Titles
Associate Professor of Biostatistics
Biography
Dr. Zhao is an Associate Professor in the Department of Biostatistics at Yale School of Public Health. She is also affiliated with Yale Department of Biomedical Informatics & Data Science, Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center, Yale Wu Tsai Institute, Yale Center for Brain and Mind Health, and Yale Computational Biology and Bioinformatics. Her main research focuses on the development of statistical and AI methods to analyze large-scale complex data (medical imaging, -omics, EHRs), Bayesian methods, feature selection, predictive modeling, data integration, missing data and network analysis. She has strong interests in biomedical research areas including mental health, psychiatry, neurodegenerative diseases, and aging. Her most recent research agenda includes analytical method development and cutting-edge scientific applications on brain-to-behavior modeling, multi-layer biomedical networks, imaging genetics and genomics, and the integration of multi-modal biomedical data with real-world data (EHRs, video, audio, etc.). Her research is supported by multiple NIH grants.
Dr. Zhao is the recipient of the prestige Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award from the Institute of Mathematical Statistics (IMS), and the COPSS Emerging Leader Award from the Committee of Presidents of Statistical Societies (COPSS). She is currently a standing member of the NIH Biodata Management and Analysis (BDMA) study section.
Appointments
Biostatistics
Associate Professor TenurePrimaryBiomedical Informatics & Data Science
Associate Professor on TermSecondary
Other Departments & Organizations
- Biomedical Informatics & Data Science
- Biostatistics
- Center for Brain & Mind Health
- Computational Biology and Biomedical Informatics
- Interdepartmental Neuroscience Program
- Neural Disorders
- Neuroscience Track
- Wu Tsai Institute
- Yale Center for Analytical Sciences (YCAS)
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)
- Yale School of Public Health
Education & Training
- PhD
- Emory University (2014)
- BS
- Zhejiang University (2010)
Research
Overview
Medical Research Interests
Public Health Interests
ORCID
0000-0001-6283-2302
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Fan Li, PhD
Denise Esserman, PhD
Erich J Greene, PhD
Todd Constable, PhD
Julian Zhao, MSPH
Can Meng, MS, MPH
Neuroimaging
Publications
2025
Cost Efficiency of fMRI Studies Using Resting‐State Vs. Task‐Based Functional Connectivity
Zhang X, Hulvershorn L, Constable T, Zhao Y, Wang S. Cost Efficiency of fMRI Studies Using Resting‐State Vs. Task‐Based Functional Connectivity. Human Brain Mapping 2025, 46: e70260. PMID: 40543060, PMCID: PMC12182254, DOI: 10.1002/hbm.70260.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsNeuroimaging studiesNeuropsychological outcomesFMRI conditionsGradual-onset continuous performance taskCognitive control outcomesN-back memory taskContinuous performance taskNegative emotional outcomesFMRI taskMemory taskFMRI studyPerformance tasksTask conditionsEmotional outcomesFMRITaskFunctional fingerprintsPower differentialsSociabilityOutcomesControl outcomesscMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links
Wang G, Zhao J, Lin Y, Liu T, Zhao Y, Zhao H. scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links. Nature Communications 2025, 16: 4994. PMID: 40442129, PMCID: PMC12122792, DOI: 10.1038/s41467-025-60333-z.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsDeep learning frameworkSingle-cell multi-omics researchSingle-cell multi-omics dataLearning frameworkMulti-omics dataGenerative adversarial networkSingle-cell technologiesData alignmentSingle-cell resolutionMulti-omics researchDownstream analysisCellular statesOmics datasetsAdversarial networkNeural networkProteomic profilingCorrelated featuresBiological informationOmics perspectiveDiverse datasetsFeature topologyDisease mechanismsCell embeddingData resourcesRelationship inferenceBayesian Longitudinal Network Regression With Application to Brain Connectome Genetics
Li C, Tian X, Gao S, Wang S, Wang G, Zhao Y, Zhao Y. Bayesian Longitudinal Network Regression With Application to Brain Connectome Genetics. Statistics In Medicine 2025, 44: e70069. PMID: 40277222, DOI: 10.1002/sim.70069.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsSample relatednessLongitudinal genome-wide association studiesGenome-wide association studiesBrain imaging genetic studiesMultivariate phenotypesGenetic signalsImaging genetics studiesAssociation studiesGenetic studiesGenetic variantsGenetic underpinningsGenetic contributionGenetic effectsRelatednessAdolescent Brain Cognitive DevelopmentBrain functional connectivityFunctional organizationBiological architectureFunctional connectivityRobust inferenceGeneticsPhenotypeAnalytical challengesPosterior inferenceBrain network configurationA genetically informed brain atlas for enhancing brain imaging genomics
Bao J, Wen J, Chang C, Mu S, Chen J, Shivakumar M, Cui Y, Erus G, Yang Z, Yang S, Wen Z, Zhao Y, Kim D, Duong-Tran D, Saykin A, Zhao B, Davatzikos C, Long Q, Shen L. A genetically informed brain atlas for enhancing brain imaging genomics. Nature Communications 2025, 16: 3524. PMID: 40229250, PMCID: PMC11997130, DOI: 10.1038/s41467-025-57636-6.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsBrain imaging genomicsImaging genomicsComplex traits/diseasesSNP heritabilityFunctional annotationGenetic architecturePolygenic risk scoresGenomic investigationsGenetic ancestryDiscovery powerBrain atlasesHuman brain structureGenetic determinantsNeuroanatomical heterogeneityGenomeNeuroanatomical variationImaging endophenotypesBrain structuresMolecular levelBrain voxelsHeritabilityPhenotypic correlationsGiant regionGeneticsBrain conditionsSemiparametric joint modeling for biomarker trajectory before disease onset
Sun Y, Zhao X, Chan K, Xu W, Allore H, Zhao Y. Semiparametric joint modeling for biomarker trajectory before disease onset. Biometrics 2025, 81: ujaf064. PMID: 40433774, PMCID: PMC12117339, DOI: 10.1093/biomtc/ujaf064.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsSemiparametric joint modelFinite-sample performanceLarge-sample propertiesConduct simulation studiesBiomarker trajectoriesNatural time scaleJoint modelEstimated regression coefficientsTime-on-studySimulation studyTrajectory functionRegression coefficientsEquationsKernelTime scalesProfile kernel
2024
Bayesian thresholded modeling for integrating brain node and network predictors
Sun Z, Xu W, Li T, Kang J, Alanis-Lobato G, Zhao Y. Bayesian thresholded modeling for integrating brain node and network predictors. Biostatistics 2024, 26: kxae048. PMID: 39780514, PMCID: PMC11823287, DOI: 10.1093/biostatistics/kxae048.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsPrediction mechanismNetwork-level metricsExtensive simulationsNetwork predictorPrior modelsSub-networksVector-variantPosterior inferenceNodesSignal patternsPredictable componentBrain nodesSpatial contiguityBayesian regression modelsImagesHierarchyLiterature gapNetworkMetricsCommunicationAlternative approachOut-of-sample predictionsInferenceModelBayesian subtyping for multi-state brain functional connectome with application on preadolescent brain cognition
Chen T, Zhao H, Tan C, Constable T, Yip S, Zhao Y. Bayesian subtyping for multi-state brain functional connectome with application on preadolescent brain cognition. Biostatistics 2024, 26: kxae045. PMID: 39656842, PMCID: PMC11823269, DOI: 10.1093/biostatistics/kxae045.Peer-Reviewed Original ResearchCitationsAltmetricConceptsAdolescent Brain Cognitive DevelopmentVariational inference algorithmApproximate posterior inferenceFunctional connectivityMultiple cognitive statesInference algorithmExtensive simulationsNetwork topologyNetwork featuresFunctional network patternsBrain functional connectomeBrain functional connectivityEstimation accuracySubgroups of individualsNeurobiological heterogeneityCognitive profileCognitive statesConverging evidencePosterior inferenceDetection alternativesNeuroscience literatureBrain cognitionFunctional connectomeNetworkCognitive developmentEffect of brain network scale on Persistence Cycles: An ADNI comparative study
Garai S, Liu M, Xu F, Goñi J, Duong‐Tran D, Zhao Y, Shen L, for the ADNI. Effect of brain network scale on Persistence Cycles: An ADNI comparative study. Alzheimer's & Dementia 2024, 20: e092343. PMCID: PMC11716291, DOI: 10.1002/alz.092343.Peer-Reviewed Original ResearchCitationsConceptsStructural connectomeFunctional connectomeBOLD signal fluctuationsBrain networksHomologation cycleAlzheimer's diseaseDiffusion tensor imagingStages of AD progressionAverage persistenceFMRI neuroimagingTopological featuresAlzheimer's Disease Neuroimaging InitiativeStages of disease progressionSignal fluctuationsConnectomeGroup differencesResolution scaleAD progressionImage resolutionResolution imagesTopological pointIncrease image resolutionDeath timeRegion-of-interestBarcodingCaudal and Thalamic Segregation in White Matter Brain Network Communities in Alzheimer's Disease Population
Xu F, Duong-Tran D, Zhao Y, Shen L. Caudal and Thalamic Segregation in White Matter Brain Network Communities in Alzheimer's Disease Population. 2024, 00: 1-8. DOI: 10.1109/bhi62660.2024.10913835.Peer-Reviewed Original ResearchConceptsStructural brain networksMild cognitive impairmentBrain networksDiffusion tensor imagingNeural correlates of cognitive deficitsCorrelates of cognitive deficitsConsensus communitiesAlzheimer's diseaseDecision-making regionsWhite matter connectivityHealthy controlsResolution parameterNeural correlatesCognitive deficitsNeuroimaging studiesBrain regionsDiagnosed AD subjectsDisconnection syndromeClinically diagnosed ADCognitive impairmentAD groupTensor imagingAD subjectsGray matterAD relationshipsSex‐specific topological structure associated with dementia via latent space estimation
Wang S, Wang Y, Xu F, Tian X, Fredericks C, Shen L, Zhao Y, Initiative F. Sex‐specific topological structure associated with dementia via latent space estimation. Alzheimer's & Dementia 2024, 20: 8387-8401. PMID: 39530632, PMCID: PMC11667551, DOI: 10.1002/alz.14266.Peer-Reviewed Original Research
Academic Achievements & Community Involvement
Activities
activity Biometrics
2022 - PresentJournal ServiceAssociate Editoractivity BMC Medical Research Methodology
2019 - PresentJournal ServiceAssociate Editoractivity Regional Advisory Board
2019 - 2022Advisory BoardsMemberDetailsInternational Biometric Society/Eastern North American Regionactivity International Biometric Society/Eastern North American Region
2021 - 2021Meeting Planning and ParticipationCo-Chair
Honors
honor COPSS Emerging Leader Award
03/01/2025International AwardCommittee of Presidents of Statistical Societieshonor Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award
01/01/2025International AwardInstitute of Mathematical Statisticshonor YSPH Investigator Research Award
05/01/2024Yale University AwardYSPHhonor Elected member
07/01/2021International AwardInternational Statistical InstituteDetailsNetherlandshonor Yale Alzheimer's Disease Research Center Research Scholar Award
06/01/2021Yale School of Medicine AwardYale Alzheimer's Disease Research CenterDetailsUnited States
News & Links
News
- January 27, 2025
Dr. Yize Zhao Receives Award for Emerging Women Leaders in Data Science
- December 20, 2024
Interdisciplinary Collaboration Yields Greater Impact
- August 29, 2024
Yale Researchers Awarded $20.6M Grant for Wide-Ranging Study of Mental Illness
- May 23, 2024
2024 Top Research Awards Announced
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New Haven, CT 06511