Faculty

Institution

Unit

Venue

Richard Scheines

Professor

University of Pittsburgh

Affiliations

Kenneth P. Dietrich School of Arts and Sciences

History and Philosophy of Science

Richard Scheines is currently serving as a History And Philosophy Of Science Professor at University of Pittsburgh.

Honors

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Experiences

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Education

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Richard Scheines

University of Pittsburgh

Professor

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statistics causal inference machine learning computer science data science causality education artificial intelligence educational research inference philosophy of science knowledge discovery educational data mining causal reasoning computing education statistical inference causal structure computational intelligence predictability microarray data analysis causal models higher education latent variable models teaching methods sociological research regression analysis causal relations causal discovery educational psychology behavioral research social science research decision science automated reasoning learning theory curriculum & instruction online learning experimental analysis ai education structure discovery student learning tetrad project tetrad program microarray data educational assessment applied cognitive psychology machine learning research applied philosophy intellectual discourse distance education biomedical informatics genome biology psychometrics estimation theory intervention mechanism evidence-based interventions constraint solving constraint programming constraint satisfaction computational learning theory supervised learning social work research self-efficacy theory mindset philosophical inquiry philosophy of education practical philosophy structural equation modeling structural coefficient bias bayesian estimation structural equation models model specification gene expression networks bayesian network models multidimensional data bottom-out hints worked examples bayesian network causal modeling technological forecasting causal relation extraction data mining science and technology studies

Notable Scholarly Works

Notable Federal Grants

Collaborators

Prediction. Springer eBooks (2020)

Virgil Zeigler-HillTodd K. Shackelford

Is the Doer Effect Robust Across Multiple Data Sets. Educational Data Mining (2018)

Kenneth R. KoedingerRichard ScheinesPeter Schaldenbrand

data miningeducationeducational data miningeducational researchmultiple data setsdoer effectmachine learning

The Limits of Causal Knowledge. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) (2018)

James M. RobinsRichard ScheinesPeter SpirtesLarry Wasserman

philosophycausal knowledgeepistemologycausality

Time and Attention: Students, Sessions, and Tasks. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) (2018)

Andrew ArnoldRichard ScheinesJoseph E. BackBill Jerome

task analysisattentionpsychologyeducationeducational psychologytime perceptionstudent learningtask performance

Finding Pure Submodels for Improved Differentiation of Bifactor and Second-Order Models. Structural Equation Modeling A Multidisciplinary Journal (2017)

Renjie YangPeter SpirtesRichard ScheinesSteven P. ReiseMaxwell Mansoff

pure submodelsmachine learningsecond-order modelsapplied mathematics

Measurement Error and Causal Discovery.. PubMed (2016)

Richard ScheinesJoseph D. Ramsey

statisticsdata sciencemeasurement errormachine learningcausal discoverybehavioral sciences

Using Tutors to Improve Educational Games: A Cognitive Game for Policy Argument. Journal of the Learning Sciences (2016)

Matthew W. EasterdayVincent AlevenRichard ScheinesSharon M. Carver

cognitive gamelearning sciencespolicy argumenteducation

The Center for Causal Discovery of Biomedical Knowledge From Big Data. Journal of the American Medical Informatics Association (2015)

Gregory F CooperIvet BaharMichael J BecichPanayiotis V BenosJeremy BergJessi EspinoClark GlymourRebecca Crowley JacobsonMichelle KienholzAdrian V LeeXinghua LuRichard Scheines

informaticsbiomedical informaticsbiomedical knowledgehealth informaticsdata sciencebig datahealth sciencescausal discovery

When Are Multidimensional Data Unidimensional Enough for Structural Equation Modeling? an Evaluation of the Detect Multidimensionality Index. Structural Equation Modeling A Multidisciplinary Journal (2015)

Wes E. BonifaySteven P. ReiseRichard ScheinesRob R. Meijer

multidimensional datadata science

Causal Clustering for 2-Factor Measurement Models. Lecture notes in computer science (2014)

Erich KummerfeldJoe RamseyRenjie YangPeter SpirtesRichard Scheines

clusteringcausal inferencecomputer science

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Richard Scheines

Professor

University of Pittsburgh

Affiliations

Kenneth P. Dietrich School of Arts and Sciences

History and Philosophy of Science

Richard Scheines is currently serving as a History And Philosophy Of Science Professor at University of Pittsburgh.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Richard Scheines

University of Pittsburgh

Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Prediction. Springer eBooks (2020)

Virgil Zeigler-HillTodd K. Shackelford

Is the Doer Effect Robust Across Multiple Data Sets. Educational Data Mining (2018)

Kenneth R. KoedingerRichard ScheinesPeter Schaldenbrand

data miningeducationeducational data miningeducational researchmultiple data setsdoer effectmachine learning

The Limits of Causal Knowledge. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) (2018)

James M. RobinsRichard ScheinesPeter SpirtesLarry Wasserman

philosophycausal knowledgeepistemologycausality

Time and Attention: Students, Sessions, and Tasks. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) (2018)

Andrew ArnoldRichard ScheinesJoseph E. BackBill Jerome

task analysisattentionpsychologyeducationeducational psychologytime perceptionstudent learningtask performance

Finding Pure Submodels for Improved Differentiation of Bifactor and Second-Order Models. Structural Equation Modeling A Multidisciplinary Journal (2017)

Renjie YangPeter SpirtesRichard ScheinesSteven P. ReiseMaxwell Mansoff

pure submodelsmachine learningsecond-order modelsapplied mathematics

Measurement Error and Causal Discovery.. PubMed (2016)

Richard ScheinesJoseph D. Ramsey

statisticsdata sciencemeasurement errormachine learningcausal discoverybehavioral sciences

Using Tutors to Improve Educational Games: A Cognitive Game for Policy Argument. Journal of the Learning Sciences (2016)

Matthew W. EasterdayVincent AlevenRichard ScheinesSharon M. Carver

cognitive gamelearning sciencespolicy argumenteducation

The Center for Causal Discovery of Biomedical Knowledge From Big Data. Journal of the American Medical Informatics Association (2015)

Gregory F CooperIvet BaharMichael J BecichPanayiotis V BenosJeremy BergJessi EspinoClark GlymourRebecca Crowley JacobsonMichelle KienholzAdrian V LeeXinghua LuRichard Scheines

informaticsbiomedical informaticsbiomedical knowledgehealth informaticsdata sciencebig datahealth sciencescausal discovery

Wes E. BonifaySteven P. ReiseRichard ScheinesRob R. Meijer

multidimensional datadata science

Causal Clustering for 2-Factor Measurement Models. Lecture notes in computer science (2014)

Erich KummerfeldJoe RamseyRenjie YangPeter SpirtesRichard Scheines

clusteringcausal inferencecomputer science

1
2
3
4
5
13
10 / page

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Similar Faculty Members

Glenn Shafer

Institution

Rutgers University–New Brunswick

uncertainty analysis

game theory

Clark Glymour

Institution

University of Pittsburgh

causal relation extraction

philosophy of mathematics

Peter Spirtes

Institution

Carnegie Mellon University

probability and causality

econometrics

Michael R Strevens

Institution

New York University

philosophy of social science

epistemology

Emma Brunskill

Institution

Stanford University

machine learning

reinforcement learning

Xiangen Hu

Institution

University of Memphis

memory studies

cognitive science

Kevin Kelly

Institution

Carnegie Mellon University

lottery paradox

mathematical logic

Kun Zhang

Institution

Carnegie Mellon University

multidisciplinary ai

causality-based learning

Nigel Bosch

Institution

University of Illinois Urbana-Champaign

fairness

user modeling