Reliability In Machine Learning Professors in Global

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Kishor Trivedi
Duke University Singapore
software reliability
reliability engineering
performability models
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Shai Ben-david
University of Waterloo Canada
reliability in machine learning
interpretability in machine learning
fairness in machine learning
machine learning
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Subham Sahoo
Aalborg University Denmark
reliability
probabilistic machine learning
scientific machine learning
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Yasmine Abdin
University of British Columbia Canada
structural reliability
machine learning
durability
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Yasmine Abdin
University of British Columbia Canada
structural reliability
machine learning
durability
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Henrik Boström
KTH Royal Institute of Technology Sweden
trustworthy machine learning
explainable machine learning
probabilistic machine learning
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Navid Azizan
Massachusetts Institute of Technology United States of America
trustworthy machine learning
machine learning
scientific machine learning
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Gjergji Kasneci
Technical University of Munich Germany
fairness in machine learning
algorithm robustness
machine learning
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning algorithms
machine learning
machine learning theory
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Danica Sutherland
University of British Columbia Canada
machine learning
theoretical machine learning
statistical machine learning
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Yingzhen Li
Imperial College London United Kingdom
explainable machine learning
machine learning
probabilistic machine learning
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Moez Ali
Queen's University Canada
model interpretability
machine learning
automated machine learning
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Michael Guerzhoy
University of Toronto Canada
machine learning
interpretable machine learning
mechanistic interpretability
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Kishor Trivedi
Duke University Singapore
reliability modeling
software reliability
performability modeling
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Baran Yeter
Aalborg University Denmark
management reliability
structural reliability
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G. Bennett
Texas A&M University United States of America
reliability
maintainability
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Kostas Kopsidas
University of Manchester United Kingdom
reliability assessment
operation reliability
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David Pan
University of Texas at Austin United States of America
reliability
machine learning
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Deepjyoti Deka
Massachusetts Institute of Technology United States of America
reliability
machine learning
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John Wilson
Western University Canada
reliability
machine learning
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Mohammad Rafiee
University of Ottawa Canada
reliability
machine learning
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