Machine Scheduling Professors in Global

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Kiefer
Technical University of Berlin Germany
scheduling models
stochastic online scheduling
mathematical optimization
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Ziv Scully
Cornell University Netherlands
scheduling
machine learning
queueing systems
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Felipe Trevizan
Australian National University Australia
scheduling
machine learning
automated planning
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Allan Larsen
Technical University of Denmark Denmark
vehicle scheduling
crew scheduling
timetabling
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Dora Shan
Australian National University Australia
stochastic scheduling
battery scheduling
optimisation modelling
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Malek Mouhoub
University of Regina Canada
scheduling and planning
machine learning
robot motion planning
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Tom Silver
Princeton University United States of America
machine learning
task motion planning
automated planning
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Moez Ali
Queen's University Canada
machine learning
automated machine learning
automated modeling
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Yisong Yue
California Institute of Technology United States of America
machine learning
statistical machine learning
structured machine learning
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Jian Jin
Purdue University United States of America
machine learning
machine vision
machine systems engineering
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Amir-hossein Karimi
University of Waterloo Canada
machine learning
human-machine teaming
human-machine collaboration
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Ilan Adler
University of California, Berkeley United States of America
computer aided scheduling
linear programming
mathematical programming
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Danica Sutherland
University of British Columbia Canada
machine learning
statistical machine learning
theoretical machine learning
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Ye Zhao
Georgia Institute of Technology United States of America
task motion planning
automation
real-time motion planning
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Zhenyu Yang
Aalborg University Denmark
machine learning
automation
process control
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Laurence Frank
Utrecht University Netherlands
machine learning
programming
predictive modelling
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Magnus Ross
University College London United Kingdom
machine learning
time series forecasting
probabilistic machine learning
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Kalyanmoy Deb
Michigan State University United States of America
machine learning
process optimization
computational optimization
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Charles Gretton
Australian National University Australia
machine learning
automated planning
optimisation
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Daniel Rakita
Yale University United States of America
machine learning
motion planning
motion optimization
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning
machine learning algorithms
machine learning theory
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