Yuan Huang, PhD
Assistant Professor of Biostatistics (Biostatistics)Cards
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Assistant Professor of Biostatistics (Biostatistics)
Biography
Yuan Huang is an Assistant Professor in the Department of Biostatistics at Yale School of Public Health. Her methodological research is focused on statistical methods for high-dimensional data and has been motivated by challenges posted by analyzing cancer genomics, such as low reproducibly, nonlinearity, and heterogeneity. Applications from her work include biomarker identification, large-scale network structure estimation, GxE analysis, etc. She is particularly interested in integrative analysis that simultaneously analyzes multiple datasets to improve the discovery. Recently she collaborates extensively in neurodegenerative diseases, such as Huntington’s disease and multiple sclerosis. She is also actively involved in collaborative research on clinical trials, genetics, epidemiology, and other biomedical fields.
Appointments
Biostatistics
Assistant ProfessorPrimary
Other Departments & Organizations
Education & Training
- PhD
- The Pennsylvania State University, Statistics
Research
Overview
Public Health Interests
Research at a Glance
Yale Co-Authors
Publications Timeline
Jingyuan Xiao, MPH, BS, BA
Nicole Deziel, PhD, MHS
Xiaomei Ma, PhD
Publications
2024
Schrödinger-Föllmer Sampler
Huang J, Jiao Y, Kang L, Liao X, Liu J, Liu Y. Schrödinger-Föllmer Sampler. IEEE Transactions On Information Theory 2024, 71: 1283-1299. DOI: 10.1109/tit.2024.3522494.Peer-Reviewed Original ResearchConceptsNon-asymptotic error boundsEuler–Maruyama discretizationMarkov chain Monte Carlo methodsEuler–MaruyamaUnit intervalError boundsWasserstein distancePosterior distributionSampling distributionNumerical experimentsUnnormalized distributionsTarget distributionMonte Carlo methodMachine learningProbability distributionBayesian inferenceDegenerate formErgodicityDiffusion processCarlo methodTheoretical analysisInferenceBoundsSFSWassersteinNonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models
Liu C, Jiao Y, Wang J, Huang J. Nonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models. SIAM Journal On Mathematics Of Data Science 2024, 6: 847-868. DOI: 10.1137/23m1598210.Peer-Reviewed Original ResearchNetwork analysis of smoking-related sleep characteristics in Chinese adults
Xie Y, Sun P, Huang H, Wu J, Ba Y, Zhou G, Yu F, Zhang D, Zhang Y, Qie R, Hu Z, Zou K, Zhang Y. Network analysis of smoking-related sleep characteristics in Chinese adults. Annals Of Medicine 2024, 56: 2332424. PMID: 38527416, PMCID: PMC10964831, DOI: 10.1080/07853890.2024.2332424.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsLate bedtimeMultiple sleep characteristicsChinese adultsCancer-related risk factorsPotential core domainsSleep characteristicsSleep health promotionLogistic regression modelsShort sleep durationHealth promotionTobacco preventionCurrent smokingSmoking cessationSmoking intensitySmoking behaviorHeavy smokingSleep durationNap timeSmokingPositive associationRisk factorsRegression modelsYoung adultsAdultsAssociationApplication of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database
Zhao L, Niu P, Wang W, Han X, Luan X, Huang H, Zhang Y, Zhao D, Gao J, Chen Y. Application of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database. Journal Of The National Cancer Center 2024, 4: 142-152. PMID: 39282580, PMCID: PMC11390701, DOI: 10.1016/j.jncc.2024.01.007.Peer-Reviewed Original ResearchConceptsCancer-specific survivalSEER validation setCancer-specific survival modelGastric cancer patientsOverall survivalArea under the curveGastrectomy patientsHigh-risk groupCancer patientsChina National Cancer Center Gastric Cancer DatabaseNational Cancer Center Gastric Cancer DatabasePrognosis predictionTumor-node-metastasis (TNM) stageEnd Results databaseGastric cancer databaseValidation setPrognostic value of risk scoreTest 6 monthsPredicting 6-monthAccurate prognosis predictionInternal validation setNeoadjuvant therapyResults databaseCancer DatabasePrognostic valueDeep Dimension Reduction for Supervised Representation Learning
Huang J, Jiao Y, Liao X, Liu J, Yu Z. Deep Dimension Reduction for Supervised Representation Learning. IEEE Transactions On Information Theory 2024, 70: 3583-3598. DOI: 10.1109/tit.2023.3340658.Peer-Reviewed Original ResearchConceptsRepresentation learningStandard deep learning modelsHigh-dimensional complex dataSupervised representation learningRepresentation learning tasksDeep neural networksEffective data representationsContext of classificationDeep learning modelsNonparametric representationDimension reduction methodDimension reduction approachLearned representationsPromote disentanglementData representationNeural networkComplex dataLearning modelsDimension reductionTarget representationLearning tasksReduction methodSufficient dimension reduction methodsLow-dimensionalConditional independence
2023
Online inference in high-dimensional generalized linear models with streaming data.
Luo L, Han R, Lin Y, Huang J. Online inference in high-dimensional generalized linear models with streaming data. Electronic Journal Of Statistics 2023, 17: 3443-3471. PMID: 39188774, PMCID: PMC11346802, DOI: 10.1214/23-ejs2182.Peer-Reviewed Original ResearchOnline inference with debiased stochastic gradient descent
Han R, Luo L, Lin Y, Huang J. Online inference with debiased stochastic gradient descent. Biometrika 2023, 111: 93-108. DOI: 10.1093/biomet/asad046.Peer-Reviewed Original ResearchConceptsStochastic gradient descent algorithmHigh-dimensional statisticsOne-pass algorithmGradient descent algorithmHigh-dimensional dataAsymptotic normalityText datasetsSparsity levelOnline fashionOnline inferenceData distributionTime complexitySpace complexityDescent algorithmStatistical inferenceUpdate stepNumerical experimentsAlgorithmDebiasing techniquesMild conditionsInferenceSparsityEstimationConfidence intervalsDatasetPhysical activity domains and patterns with risk of depressive symptoms: A cross-sectional study in China
Qie R, Huang H, Sun P, Wu J, Ba Y, Zhou G, Yu F, Zhang D, Zhang Y, Xie Y, Hu Z, Zou K, Zhang Y. Physical activity domains and patterns with risk of depressive symptoms: A cross-sectional study in China. Journal Of Affective Disorders 2023, 337: 120-127. PMID: 37263360, DOI: 10.1016/j.jad.2023.05.091.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsLeisure-time PARisk of depressive symptomsTransportation PAPA patternsHousehold PADepressive symptomsCross-sectional studyOccupational PAOdds ratioPhysical activityDomain-specific physical activityPhysical activity domainsConfidence intervalsCalculate odds ratiosCross-sectional designNon-linear associationPA domainsLogistic regression analysisInverse associationInactive groupInconsistent associationsLatent class analysisPositive associationHealth benefitsLow riskDeep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors
Jiao Y, Shen G, Lin Y, Huang J. Deep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors. The Annals Of Statistics 2023, 51 DOI: 10.1214/23-aos2266.Peer-Reviewed Original ResearchPhysical activity and risk of lung cancer: A systematic review and dose-response meta-analysis of cohort studies
Qie R, Han M, Huang H, Sun P, Xie Y, He J, Zhang Y. Physical activity and risk of lung cancer: A systematic review and dose-response meta-analysis of cohort studies. Journal Of The National Cancer Center 2023, 3: 48-55. PMID: 39036308, PMCID: PMC11256557, DOI: 10.1016/j.jncc.2022.12.003.Peer-Reviewed Original ResearchConceptsLeisure-time physical activityOccupational physical activityLung cancer riskCancer riskPhysical activityMetabolic equivalent of task hoursLeisure-time physical activity levelsDose-response meta-analysis of cohort studiesIncident cases of lung cancerMeta-analysis of cohort studiesRisk of lung cancerConfidence intervalsDose-response meta-analysisApproximately U-shaped associationU-shaped associationLung cancerMetabolic equivalentsCases of lung cancerWeb of ScienceDose-response analysisIncident casesFixed-effects modelStanding occupationCancer associationStudy participants
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