Faculty

Institution

Unit

Venue

Peter Spirtes

Department Head and Professor

Carnegie Mellon University

Affiliations

Dietrich College of Humanities and Social Sciences

Philosophy

Peter Spirtes is currently serving as a Dietrich College Of Humanities And Social Sciences Department Head and Professor at Carnegie Mellon University.

Honors

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Experiences

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Education

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Peter Spirtes

Carnegie Mellon University

Department Head and Professor

You can click a keyword to filter the displayed items

machine learning causal inference statistics computer science data science causality inference graph theory statistical inference causal reasoning causal models behavioral sciences latent variables artificial intelligence causal discovery statistical methodology knowledge discovery predictability latent variable models causal structure causal effects probabilistic graph theory directed graphs markov equivalence bioinformatics probability theory computational intelligence machine learning research bayesian analysis microarray data analysis structure discovery respiratory medicine social science research combinatorial theory bayesian inference selection bias sociological research regression analysis causal diagrams uniform consistency conditional independence measurement error markov equivalence classes transformational characterization linear non-gaussian models behavioral research scientometrics bibliometrics learning theory supervised learning feedback loop sparse causal graphs tetrad project applied cognitive psychology health planning intensive care public health preparedness biomedical informatics approximate reasoning graph analysis constraint programming constraint satisfaction constraint solving service life prediction computational learning theory deception detection response prediction prognosis disease assessment disease risk assessment disease management case studies community health neuroinformatics fast recovery causal discovery methods causal relationships sociology causal relation extraction analytics epidemiology social simulation political science econometrics

Notable Scholarly Works

Notable Federal Grants

Collaborators

Causal Discovery and Counterfactual Reasoning to Optimize Persuasive Dialogue Policies. Behaviour and Information Technology (2025)

inferenceconversation analysiscommunicationcognitive sciencepersuasioncausal discoverycausal reasoningcausal relation extractiondecision sciencebehavioral decision makingcausal inferencebehavioral sciencesdialogue management

Corrigendum to “Estimating Bounds on Causal Effects in High-Dimensional and Possibly Confounded Systems” [Int. J. Approx. Reason. 88 (2017) 371–384]. International Journal of Approximate Reasoning (2025)

statistical inferencestatisticsinferencehigh-dimensional statisticsstatistical methodologyestimation statisticcausalitycomputational statisticscausal reasoningcausal modelscausal relation extractionstatistical modelsapplied mathematicsapplied statisticscausal effectscausal inference

Generative Framework for Personalized Persuasion: Inferring Causal, Counterfactual, and Latent Knowledge. (2025)

inferencecommunicationpersuasive technologygenerative frameworkpersuasioncognitive sciencelatent knowledgecausal reasoningcausal modelsrecommender systemspersonalized persuasionattitude theorybehavioral decision makingsocial influencecausal inferencebehavioral sciencesbias

Causal Discovery and Epidemiology: A Potential for Synergy. American Journal of Epidemiology (2024)

Anne Helby PetersenClaus Thorn EkstrømPeter SpirtesMerete Osler

causal discoverycausal inferenceepidemiology

Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome. Lecture notes in computer science (2024)

Donghuo ZengRoberto S. LegaspiYuewen SunXinshuai DongKazushi IkedaPeter SpirtesKun Zhang

computer sciencepersuasion outcomelatent personality dimensionscomputational social sciencepersuasionpsychometrics

Gene Regulatory Network Inference in the Presence of Dropouts: A Causal View. arXiv (Cornell University) (2024)

Dai, HaoyueNg, IgnavierLuo, GongxuSpirtes, PeterStojanov, PetarZhang, Kun

geneticsgene regulationgene regulatory networkssystems biologycausal viewevolutionary biologycausal inference

A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. arXiv (Cornell University) (2023)

Dong, XinshuaiHuang, BiweiNg, IgnavierSong, XiangchenZheng, YujiaJin, SongyaoLegaspi, RobertoSpirtes, PeterZhang, Kun

machine learningcomputer sciencecausally-related hidden variables

Causal Discovery for Observational Sciences Using Supervised Machine Learning. Journal of Data Science (2023)

Anne Helby PetersenJoseph RamseyClaus Thorn EkstrømPeter Spirtes

machine learningobservational sciencescausal discoverydata sciencesupervised machine learning

Causal-Learn: Causal Discovery in Python. arXiv (Cornell University) (2023)

Zheng, YujiaHuang, BiweiChen, WeiRamsey, JosephGong, MingmingCai, RuichuShimizu, ShoheiSpirtes, PeterZhang, Kun

machine learningcomputer sciencecausal discoveryinformatics

Constructing Causal Life-Course Models: Comparative Study of Data-Driven and Theory-Driven Approaches. American Journal of Epidemiology (2023)

Anne Helby PetersenClaus Thorn EkstrømPeter SpirtesMerete Osler

epidemiologydata sciencecausal life-course modelslife coursepublic healthcomparative studydata-driven science

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Peter Spirtes

Department Head and Professor

Carnegie Mellon University

Affiliations

Dietrich College of Humanities and Social Sciences

Philosophy

Peter Spirtes is currently serving as a Dietrich College Of Humanities And Social Sciences Department Head and Professor at Carnegie Mellon 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

Peter Spirtes

Carnegie Mellon University

Department Head and Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Causal Discovery and Counterfactual Reasoning to Optimize Persuasive Dialogue Policies. Behaviour and Information Technology (2025)

Generative Framework for Personalized Persuasion: Inferring Causal, Counterfactual, and Latent Knowledge. (2025)

Causal Discovery and Epidemiology: A Potential for Synergy. American Journal of Epidemiology (2024)

Anne Helby PetersenClaus Thorn EkstrømPeter SpirtesMerete Osler

causal discoverycausal inferenceepidemiology

Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome. Lecture notes in computer science (2024)

Donghuo ZengRoberto S. LegaspiYuewen SunXinshuai DongKazushi IkedaPeter SpirtesKun Zhang

computer sciencepersuasion outcomelatent personality dimensionscomputational social sciencepersuasionpsychometrics

Gene Regulatory Network Inference in the Presence of Dropouts: A Causal View. arXiv (Cornell University) (2024)

Dai, HaoyueNg, IgnavierLuo, GongxuSpirtes, PeterStojanov, PetarZhang, Kun

geneticsgene regulationgene regulatory networkssystems biologycausal viewevolutionary biologycausal inference

A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. arXiv (Cornell University) (2023)

Dong, XinshuaiHuang, BiweiNg, IgnavierSong, XiangchenZheng, YujiaJin, SongyaoLegaspi, RobertoSpirtes, PeterZhang, Kun

machine learningcomputer sciencecausally-related hidden variables

Causal Discovery for Observational Sciences Using Supervised Machine Learning. Journal of Data Science (2023)

Anne Helby PetersenJoseph RamseyClaus Thorn EkstrømPeter Spirtes

machine learningobservational sciencescausal discoverydata sciencesupervised machine learning

Causal-Learn: Causal Discovery in Python. arXiv (Cornell University) (2023)

Zheng, YujiaHuang, BiweiChen, WeiRamsey, JosephGong, MingmingCai, RuichuShimizu, ShoheiSpirtes, PeterZhang, Kun

machine learningcomputer sciencecausal discoveryinformatics

Constructing Causal Life-Course Models: Comparative Study of Data-Driven and Theory-Driven Approaches. American Journal of Epidemiology (2023)

Anne Helby PetersenClaus Thorn EkstrømPeter SpirtesMerete Osler

epidemiologydata sciencecausal life-course modelslife coursepublic healthcomparative studydata-driven science

1
2
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5
19
10 / page

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intrinsic low dimensionality

granular computing

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Institution

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philosophical inquiry

philosophy of science

Kun Zhang

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multidisciplinary ai

causality-based learning

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computational optimization

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computational intelligence

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causal bayes nets

causal reasoning

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biological computation

computational biology

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economic behavior