Faculty

Institution

Unit

Venue

David Ruppert

Andrew Schultz Jr Professor of Engineering Professor

Cornell University

Affiliations

College of Engineering

School of Operations Research and Information Engineering

College of Computing and Information Science

Department of Statistics and Data Science

David Ruppert is currently serving as a College Of Engineering Andrew Schultz Jr Professor of Engineering Professor at Cornell University.

Honors

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Experiences

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Education

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David Ruppert

Cornell University

Andrew Schultz Jr Professor of Engineering Professor

You can click a keyword to filter the displayed items

statistics statistical methodology applied statistics statistical inference statistical models computational statistics estimation theory applied mathematics biostatistics model selection estimation statistic bayesian analysis regression analysis data science semi-nonparametric estimation parameter estimation high-dimensional statistics spline (mathematics) statistical theory density estimation mathematical optimization applied probability multivariate approximation asymptotic analysis bayesian hierarchical modeling curve fitting statistical modeling robust statistics bayesian statistics multivariate analysis statistical software bayesian inference machine learning research kernel methods mathematical statistics stochastic optimization high-dimensional method finance research financial econometrics computational optimization stochastic systems reproducing kernel methods statistical science financial modeling measurement error least squares financial studies spatial statistical analysis financial time series analysis regression splines regression model semiparametric regression fish biology knowledge discovery atmospheric measurement technique quantitative management stochastic calculus measurement theory gaussian process dimensionality reduction robust estimation variance function maximum likelihood nonparametric regression atlantic menhaden likelihood ratio tests molecular metabolism fishery research developmental science empirical finance model comparison american statistical association heteroscedastic regression models probabilistic networks expert systems p. 1524 functional data analysis measurement error models statistical analysis financial engineering data analytics

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Novel Approach to Assessing the Joint Effects of Mercury and Fish Consumption on Neurodevelopment in the New Bedford Cohort. American Journal of Epidemiology (2024)

Sally W ThurstonDavid RuppertSusan A Korrick

public healthdevelopmental epidemiologyfish biologyenvironmental healthearly life exposuresenvironmental exposuresmaternal healthfisheriestoxicologyneurodevelopmental disordersdietary exposuredevelopmental toxicologyenvironmental epidemiologypediatricsenvironmental health perspectivefish exposurehealth sciencesboston naming test

Bayesian Functional Data Analysis in Astronomy. arXiv (Cornell University) (2024)

Loredo, ThomasBudavari, TamasKent, DavidRuppert, David

observational astronomyastroinformaticsastrophysicsbayesian fdaplanetary sciencesastrophysical simulationsscientific dataastrostatisticsastronomybayesian analysisstatistical methodologyfunctional data analysisbayesian fda frameworkobservational cosmologycomputational statisticscosmic demographics

Correction to: Dynamic Shrinkage Processes. Journal of the Royal Statistical Society Series B (Statistical Methodology) (2024)

Daniel R KowalDavid S MattesonDavid Ruppert

stochastic dynamical systemsstochastic phenomenadynamic shrinkage processesdynamical systemsstochastic processasymptotic analysisapplied mathematicsstatistical mechanicsdynamic processnonlinear dynamicsmathematics

Bayesian Functional Principal Components Analysis via Variational Message Passing With Multilevel Extensions. Bayesian Analysis (2023)

Tui H. NolanJeff GoldsmithDavid Ruppert

scientific computingvariational messagehigh-dimensional statisticsprincipal component analysisapplied statisticsvariational message passingbayesian hierarchical modelingfunctional datastatistical inferencebayesian analysisstatisticsstatistical methodologyfunctional data analysisdata sciencegraphical modelscomputational statisticsstatistical models

Characterization of Extrasolar Giant Planets With Machine Learning. Monthly Notices of the Royal Astronomical Society Letters (2023)

Jiayin LiLisa KalteneggerDang PhamDavid Ruppert

atmospheric measurement techniqueastrophysicsexoplanetsplanetary sciencesexoplanet formationextrasolar giant planetsgiant planetsatmospheric researchplanetary scienceplanetary systemsextrasolar systemastronomymachine learning researchobservational astronomymachine learningexoplanet atmospheres

Maximizing Portfolio Predictability With Machine Learning. arXiv (Cornell University) (2023)

Pinelis, MichaelRuppert, David

predictive analyticsportfolio allocationportfolio choiceportfolio optimizationmachine learningrandom forestinvestment managementfinanceportfolio managementportfolio predictabilitymachine learning researchforecastingcomputer science

Measurement Errors in Semi‐Parametric Generalised Regression Models. Australian & New Zealand Journal of Statistics (2023)

Mohammad W. HattabDavid Ruppert

applied statisticsestimation theorymeasurement errorsregression modelsregression modelstatistical inferencebiostatisticsstatisticsbayesian analysisstatistical methodologyparameter estimationestimation statisticregression analysisstatistical models

Proteomics and Cytokine Analyses Distinguish Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Cases From Controls. Journal of Translational Medicine (2023)

Ludovic GiloteauxJiayin LiMady HornigW. Ian LipkinDavid RuppertMaureen R. Hanson

immunologyextracellular microvesiclesproteomicsautoimmune diseasescellular physiologyimmunologic diseasesproteome researchclinical proteomicscytokinesextracellular vesiclesev characteristicscell biologyprotein pathwaysinflammation

Smoothness-Penalized Deconvolution (Sped) of a Density Estimate. Journal of the American Statistical Association (2023)

David KentDavid Ruppert

smoothness-penalized deconvolutiondensity estimationadditive measurement errorsapplied statisticsestimation theorydensity estimatestatistical inferencedeconvolutionstatisticsstatistical methodologyapplied mathematicscomputational statisticsapproximation theory

Splines 'N Lines: Rest-Frame Galaxy Spectral Energy Distributions via Bayesian Functional Data Analysis. arXiv (Cornell University) (2023)

Kent, DavidBudavári, TamásLoredo, Thomas J.Ruppert, David

scientific computingspectral energy distributionsrest frameextragalactic astronomyastrophysical simulationscosmologyastrostatisticsastronomybayesian analysisgalaxy formationstatistical methodologyfunctional data analysisdata sciencehierarchical bayesian frameworkobservational cosmologycomputational statisticslarge scale structuregalaxy formation and evolution

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David Ruppert

Andrew Schultz Jr Professor of Engineering Professor

Cornell University

Affiliations

College of Engineering

School of Operations Research and Information Engineering

College of Computing and Information Science

Department of Statistics and Data Science

David Ruppert is currently serving as a College Of Engineering Andrew Schultz Jr Professor of Engineering Professor at Cornell University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

David Ruppert

Cornell University

Andrew Schultz Jr Professor of Engineering Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Novel Approach to Assessing the Joint Effects of Mercury and Fish Consumption on Neurodevelopment in the New Bedford Cohort. American Journal of Epidemiology (2024)

Sally W ThurstonDavid RuppertSusan A Korrick

Bayesian Functional Data Analysis in Astronomy. arXiv (Cornell University) (2024)

Loredo, ThomasBudavari, TamasKent, DavidRuppert, David

Correction to: Dynamic Shrinkage Processes. Journal of the Royal Statistical Society Series B (Statistical Methodology) (2024)

Daniel R KowalDavid S MattesonDavid Ruppert

Bayesian Functional Principal Components Analysis via Variational Message Passing With Multilevel Extensions. Bayesian Analysis (2023)

Tui H. NolanJeff GoldsmithDavid Ruppert

Characterization of Extrasolar Giant Planets With Machine Learning. Monthly Notices of the Royal Astronomical Society Letters (2023)

Jiayin LiLisa KalteneggerDang PhamDavid Ruppert

Maximizing Portfolio Predictability With Machine Learning. arXiv (Cornell University) (2023)

Pinelis, MichaelRuppert, David

Measurement Errors in Semi‐Parametric Generalised Regression Models. Australian & New Zealand Journal of Statistics (2023)

Mohammad W. HattabDavid Ruppert

Proteomics and Cytokine Analyses Distinguish Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Cases From Controls. Journal of Translational Medicine (2023)

Ludovic GiloteauxJiayin LiMady HornigW. Ian LipkinDavid RuppertMaureen R. Hanson

Smoothness-Penalized Deconvolution (Sped) of a Density Estimate. Journal of the American Statistical Association (2023)

David KentDavid Ruppert

Splines 'N Lines: Rest-Frame Galaxy Spectral Energy Distributions via Bayesian Functional Data Analysis. arXiv (Cornell University) (2023)

Kent, DavidBudavári, TamásLoredo, Thomas J.Ruppert, David

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geographical information science

spatial analysis

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econometric model

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bayesian inference

bayesian analysis

Svetlozar Rachev

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mixture modeling

latent space estimation

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