Biostatistical Inference Professors in Global

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Dae Ham
University of Michigan United States of America
randomization inference
causal inference
adaptive sequential inference
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Guanyu Hu
Michigan State University United States of America
big data inference
causal inference
bayesian computation
bayesian nonparametric
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Peter Mueller
University of Texas at Austin United States of America
bayesian bioinformatics
nonparametric bayesian inference
computational methods in bayesian inference
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Yazhen Wang
University of Wisconsin–Madison United States of America
high-dimensional statistical inference
machine learning
order restricted statistical inferences
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Elias Bareinboim
Purdue University United States of America
causal inference
counterfactual inference
machine learning
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Fan Yang
University College London United Kingdom
causal inference
statistical models
machine learning
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Xavier De Luna
Umeå University Sweden
causal inference
statistical models
machine learning
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Wei Jin
Boston University United States of America
biostatistics
causal inference
bayesian statistical methods
machine learning
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Samrachana Adhikari
New York University United States of America
causal inference
machine learning
predictive modeling
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Thomas Icard
Stanford University United States of America
causal inference
machine learning
probabilistic reasoning
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Jayadev Acharya
Cornell University Netherlands
information-constrained inference
machine learning
algorithmic information theory
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Guotao Ma
University of Warwick United Kingdom
machine learning
probabilistic analysis
computational modeling
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Mohammad Asghari-jafarabadi
Monash University Australia
biostatistics
machine learning
clinical biostatistics
deep learning models
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Veronika Rockova
University of Chicago United States of America
predictive inference
bayesian statistics
machine learning
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Galen Reeves
Duke University Singapore
high-dimensional statistical inference
machine learning
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Dan Nicolae
University of Chicago United States of America
high-dimensional statistical inference
machine learning
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Jiaming Xu
Duke University Singapore
high-dimensional statistical inference
machine learning
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Geoff Nicholls
University of Oxford United Kingdom
applied bayesian inference
bayesian statistical methods
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Subha Kalyaanamoorthy
University of Waterloo Canada
phylogenetic inference
machine learning
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Minh Bui
Australian National University Australia
phylogenetic inference
computational phylogenomics
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Christian Frier
Aalborg University Denmark
probabilistic modeling
stochastic modeling
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