Revenue Forecasting Professors in Global

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Lennart Baardman
University of Michigan United States of America
revenue management
predictive techniques
mathematical modeling
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Peder Bacher
Technical University of Denmark Denmark
solar power forecasting
forecasting heat load
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Stefanus Jasin
University of Michigan United States of America
revenue management
predictive analytics
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R. Wilson
Michigan State University United States of America
new product forecasting
predictive analytics
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Amir Hosseinipour
Concordia University Canada
revenue management
business modelling
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Le Chang
Australian National University Australia
mortality forecasting
model averaging
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Tarek Abdallah
Northwestern University United States of America
revenue management
demand estimation
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Dalibor Cavar
Technical University of Denmark Denmark
wind energy forecasting
numerical weather prediction
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Da Zhao
University of Melbourne Australia
predictive modeling
statistical modeling
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Polina Golland
Massachusetts Institute of Technology United States of America
predictive modeling
statistical modeling
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Sylvain Sardy
University of Geneva Switzerland
predictive modeling
regression
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Mathias Rysgaard
Aalborg University Denmark
predictive modeling
mathematical modeling
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Al Barr
California Institute of Technology United States of America
predictive modeling
mathematical modeling
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Jaime Ide
Yale University United States of America
predictive modeling
theoretical modeling
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Manfred Kronz
Friedrich-Alexander-Universität Erlangen-Nürnberg Germany
predictive analytics
statistical modeling
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Saber Salehkaleybar
Leiden University Netherlands
predictive analytics
statistical modeling
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Minh Huynh
Monash University Australia
predictive analytics
statistical modeling
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Chih-ying Chen
Singapore Management University Singapore
financial reporting
analyst forecasts
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Ruby Brownen-trinh
University of Bristol United Kingdom
earnings forecasts
financial reporting
financial analysts' forecasts
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Paula Branco
University of Ottawa Canada
predictive analytics
rare extreme values forecasting
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Catherine Gorle
Stanford University United States of America
computational predictions
predictive flow simulations
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