Yize Zhao, PhD
Associate Professor of BiostatisticsDownloadHi-Res Photo
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Biostatistics
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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 Center for Analytical Sciences, Yale Alzheimer's Disease Research Center and Yale Computational Biology and Bioinformatics. Her main research focuses on the development of statistical and machine learning methods to analyze large-scale complex data (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, mental disorders and aging, etc. Her most recent research agenda includes analytical method development and applications on brain network analyses, multimodal imaging modeling, imaging genetics, and the integration of biomedical data with EHR data. Her research is supported by multiple NIH grants.
Dr. Zhao received her Ph.D. in Biostatistics from Emory University and postdoc training at Statistical and Applied Mathematical Sciences Institute (SAMSI) and the University of North Carolina at Chapel Hill. Prior to coming to Yale, she was an Assistant Professor in Biostatistics at Cornell University, Weill Cornell Medicine.
Appointments
Biostatistics
Associate Professor TenurePrimaryBiomedical Informatics & Data Science
Associate Professor on TermSecondary
Other Departments & Organizations
Education & Training
- PhD
- Emory University (2014)
- BS
- Zhejiang University (2010)
Research
Overview
Medical Subject Headings (MeSH)
Aging; Biomedical Research; Biostatistics; Electronic Health Records; Genetics; Mental Health; Neurodegenerative Diseases; Neuroimaging; Psychiatry
Research at a Glance
Yale Co-Authors
Frequent collaborators of Yize Zhao's published research.
Publications Timeline
A big-picture view of Yize Zhao's research output by year.
Research Interests
Research topics Yize Zhao is interested in exploring.
Erich J Greene, PhD
Fan Li, PhD
Julian Zhao, MSPH
Can Meng, MS, MPH
Denise Esserman, PhD
Ondrej Blaha, PhD
45Publications
211Citations
Neuroimaging
Publications
2024
Collaborative Survival Analysis on Predicting Alzheimer’s Disease Progression
Xu W, Wang S, Shen L, Zhao Y. Collaborative Survival Analysis on Predicting Alzheimer’s Disease Progression. Statistics In Biosciences 2024, 1-24. DOI: 10.1007/s12561-024-09459-0.Peer-Reviewed Original ResearchConceptsAlzheimer's diseaseGenes associated with neuronal developmentAlzheimer's Disease Neuroimaging InitiativeGenetic dataAlzheimer's disease progressionGenetic variationPhenotypic varianceAD progressionGenetic featuresNeuronal developmentGenetic biomarkersAlzheimerADNI databaseMild cognitive impairmentSNPsCanonical correlation analysisGenesStructural MRI scansCombination of brain imagingBrain imagingGeneticsProgression of mild cognitive impairmentAD literatureTime-to-event outcomesTime-to-event predictionsVolume-Optimal Persistence Homological Scaffolds of Hemodynamic Networks Covary with MEG Theta-Alpha Aperiodic Dynamics
Nguyen N, Hou T, Amico E, Zheng J, Huang H, Kaplan A, Petri G, Goñi J, Kaufmann R, Zhao Y, Duong-Tran D, Shen L. Volume-Optimal Persistence Homological Scaffolds of Hemodynamic Networks Covary with MEG Theta-Alpha Aperiodic Dynamics. Lecture Notes In Computer Science 2024, 15003: 519-529. DOI: 10.1007/978-3-031-72384-1_49.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingHigher-order propertiesHuman Connectome Project Young Adult datasetDistribution of cavitiesAperiodic dynamicsAperiodic activityFunctional magnetic resonance imaging dataFunctional connectomePairwise interactionsConnectomeSpatial distribution of cavitiesDynamic insightsTask-positive stateHomologous scaffoldsSpatial distributionStatePersistent homologyMagnetoencephalographyInduced connectionResting stateNeuroimaging modalitiesYoung Adult datasetCortical regionsSelf‐reported hearing loss is associated with faster cognitive and functional decline but not diagnostic conversion in the ADNI cohort
Miller A, Sharp E, Wang S, Zhao Y, Mecca A, van Dyck C, O'Dell R, Initiative F. Self‐reported hearing loss is associated with faster cognitive and functional decline but not diagnostic conversion in the ADNI cohort. Alzheimer's & Dementia 2024 PMID: 39324520, DOI: 10.1002/alz.14252.Peer-Reviewed Original ResearchAltmetricConceptsSelf-reported hearing lossFunctional Activities QuestionnaireHearing lossMild cognitive impairmentModifiable risk factorsMild cognitive impairment participantsFunctional declineImpairment diagnosisModified Preclinical Alzheimer Cognitive CompositeRate of functional declineRate of cognitive declinePreclinical Alzheimer Cognitive CompositeRisk factorsCognitive impairmentSignificant longitudinal associationsActivity QuestionnaireLongitudinal associationsAlzheimer's Disease Neuroimaging InitiativeLongitudinal relationshipCognitive compositeCN participantsIncreased riskCognitive declineParticipantsDiagnostic conversionA Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits
Duong-Tran D, Nguyen N, Mu S, Chen J, Bao J, Xu F, Garai S, Cadena-Pico J, Kaplan A, Chen T, Zhao Y, Shen L, Goñi J. A Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits. Mathematics 2024, 12: 2967. PMID: 38979488, PMCID: PMC11230349, DOI: 10.3390/math12192967.Peer-Reviewed Original ResearchAltmetricConceptsStochastic block modelMultiple levels of granularityLevels of granularityFunctional networksInformation-theoreticThreshold methodThreshold strategyFunctional connectomeSub-circuitsGranularityHuman brain connectomeNetworkHuman Connectome ProjectBlock modelBrain connectome analysisFunctional sub-circuitsTopological featuresFrameworkPrinciples frameworkConnectome ProjectBrain connectomeNetwork neuroscienceThreshold valueMultiple levelsPartitioningEstablishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling
Wang S, Wang Y, Xu F, Shen L, Zhao Y, Initiative A. Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling. Medical Image Analysis 2024, 99: 103309. PMID: 39243600, DOI: 10.1016/j.media.2024.103309.Peer-Reviewed Original ResearchConceptsBrain structural connectivityBrain connectivityStructural connectivityBrain connectivity matricesDiffusion MRITopological propertiesGenerative network modelsWhite matter fiber tractsAttributes of nodesConnectivity estimatesBrain networksGroup-level connectivityConnectivity matrixBrain regionsConnectivity architectureKnowledge of nodesAlzheimer's diseaseLatent space modelAnatomical informationGroup-level effectsImprove biological interpretationExtensive simulationsNetwork modelABC modelMultiscale Estimation of Morphometricity for Revealing Neuroanatomical Basis of Cognitive Traits
Wen Z, Bao J, Yang S, Wen J, Zhan Q, Cui Y, Erus G, Yang Z, Thompson P, Zhao Y, Davatzikos C, Shen L. Multiscale Estimation of Morphometricity for Revealing Neuroanatomical Basis of Cognitive Traits. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2024, 00: 1-5. PMID: 39371474, PMCID: PMC11452152, DOI: 10.1109/isbi56570.2024.10635581.Peer-Reviewed Original ResearchKnowledge-guided learning methods for integrative analysis of multi-omics data
Li W, Ballard J, Zhao Y, Long Q. Knowledge-guided learning methods for integrative analysis of multi-omics data. Computational And Structural Biotechnology Journal 2024, 23: 1945-1950. PMID: 38736693, PMCID: PMC11087912, DOI: 10.1016/j.csbj.2024.04.053.Peer-Reviewed Original ResearchCitationsAltmetricConceptsAnalysis of multi-omics dataIntegrative analysis of multi-omics dataMulti-omics dataMulti-omics data integration methodBiological knowledgeMulti-omics data integrationMulti-omics data analysisMulti-omics studiesIntegrated analysisFunctional genomicsFunctional proteomicsData integration methodsComplex diseasesMolecular mechanismsAlzheimer's diseaseComprehensive insightGenomeProteomicsGenesAnalytical challengesPathwayAlzheimerBayesian mixed model inference for genetic association under related samples with brain network phenotype
Tian X, Wang Y, Wang S, Zhao Y, Zhao Y. Bayesian mixed model inference for genetic association under related samples with brain network phenotype. Biostatistics 2024, 25: 1195-1209. PMID: 38494649, DOI: 10.1093/biostatistics/kxae008.Peer-Reviewed Original ResearchConceptsSample relatednessGenetic studiesGenetic association studiesRisk genetic variantsImaging genetics studiesPopulation structureAssociation studiesQuantitative phenotypesQuantitative geneticsGenetic basisGenetic variantsGenetic associationGenetic contributionPhenotypeRelatednessConnectivity traitsNetwork phenotypesConnectivity phenotypesMarkov chain Monte CarloMixed-effects modelsPedigreeGeneticsBiological structuresTraitsHuman Connectome ProjectHeterogeneity Analysis on Multi-State Brain Functional Connectivity and Adolescent Neurocognition
Wang S, Constable T, Zhang H, Zhao Y. Heterogeneity Analysis on Multi-State Brain Functional Connectivity and Adolescent Neurocognition. Journal Of The American Statistical Association 2024, 119: 851-863. PMID: 39371422, PMCID: PMC11451334, DOI: 10.1080/01621459.2024.2311363.Peer-Reviewed Original ResearchBayesian semi-parametric inference for clustered recurrent events with zero inflation and a terminal event
Tian X, Ciarleglio M, Cai J, Greene E, Esserman D, Li F, Zhao Y. Bayesian semi-parametric inference for clustered recurrent events with zero inflation and a terminal event. Journal Of The Royal Statistical Society Series C (Applied Statistics) 2024, 73: 598-620. PMID: 39072299, PMCID: PMC11271983, DOI: 10.1093/jrsssc/qlae003.Peer-Reviewed Original ResearchConceptsSemi-parametric inferenceRecurrent eventsAccelerated failure time modelFailure time modelEfficient sampling algorithmFrailty distributionDirichlet processPosterior inferenceSampling algorithmTime modelTerminal eventSurvival processesComplex data structuresDirichletInferenceData structureFall injury preventionAlgorithm
Academic Achievements & Community Involvement
activity Biometrics
Journal ServiceAssociate EditorDetails2022 - Presentactivity BMC Medical Research Methodology
Journal ServiceAssociate EditorDetails2019 - Presenthonor YSPH Investigator Research Award
Yale University AwardYSPHDetails05/01/2024activity Regional Advisory Board
Advisory BoardsMemberDetailsInternational Biometric Society/Eastern North American Region2019 - 2022honor Elected member
International AwardInternational Statistical InstituteDetails07/01/2021Netherlands
News & Links
News
- August 29, 2024
Yale Researchers Awarded $20.6M Grant for Wide-Ranging Study of Mental Illness
- May 23, 2024
2024 Top Research Awards Announced
- January 10, 2023
Award-winning Associate Professor Yize Zhao Applies Innovative Statistical Methods to Advance Medical Science
- February 10, 2022
YSPH grant awards top $60 million in fiscal 2021
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