Machine Learning In Law Professors in Global

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Tal Kachman
Radboud University Netherlands
machine learning
financial machine learning
deep learning
reinforcement learning
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Nicholas Rhinehart
University of Toronto Canada
machine learning
robot learning
deep learning
reinforcement learning
imitation learning
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Pieter Abbeel
University of California, Berkeley United States of America
deep learning
reinforcement learning
imitation learning
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Mehrdad Mahdavi
Pennsylvania State University United States of America
large-scale machine learning
deep learning
computational statistical machine learning
computational learning theory
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Jason Klusowski
Princeton University United States of America
deep learning
decision tree learning
statistical learning
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Sasan Barak
University of Southampton United Kingdom
machine learning applications in finance
financial machine learning
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Ed Walters
University of Chicago Law School United States of America
data-driven law
legal informatics
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Marzyeh Ghassemi
Massachusetts Institute of Technology United States of America
behavioral machine learning
healthcare machine learning
representation learning
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Marzyeh Ghassemi
Massachusetts Institute of Technology United States of America
behavioral machine learning
healthcare machine learning
representation learning
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Pierre-andré Côté
University of Montreal Canada
theory of law
law
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Jaap Van Den Herik
Leiden University Netherlands
legal informatics
law
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Varun Kanade
University of Oxford United Kingdom
computational learning
deep learning
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John Villasenor
University of California Los Angeles United States of America
law
technology and law
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Liv Henningsen
University of Southern Denmark Denmark
law
legal methodologies
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Robert George
Princeton University United States of America
law
natural law theory
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Kenworthey Bilz
University of Illinois United States of America
law
psychology and law
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Sarath Anbil Parthipan
Université de Montréal Canada
deep learning
reinforcement learning
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Yangchen Pan
University of Oxford United Kingdom
machine learning
deep learning
reinforcement learning
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Janarthanan Rajendran
Dalhousie University Canada
deep learning
reinforcement learning
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Sidney Givigi
Queen's University Canada
machine learning
deep learning
reinforcement learning
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Hongyang Dong
University of Warwick United Kingdom
machine learning
deep learning
reinforcement learning
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