Data Overload Professors in Global

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Arman Sabbaghi
Purdue University United States of America
massive data
missing data
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Heather Miller
Carnegie Mellon University United States of America
data-intensive systems
big data
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Markus Pelger
Stanford University United States of America
big data problems
high-dimensional data
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Peng Ding
University of California, Berkeley United States of America
contaminated data
missing data
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Alex Kuo
University of Victoria Canada
big data
data warehousing
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Xiufeng Liu
Technical University of Denmark Denmark
big data
data warehousing
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Mostafa Milani
Western University Canada
data cleaning
data quality
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Christie Ezeife
University of Windsor Canada
data warehousing
data fragmentation
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Carole Del Degan
ZHAW Zurich University of Applied Sciences Switzerland
data processing
data exchange
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Peter Lugtig
Utrecht University Netherlands
data quality
data fusion
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Sepehr Assadi
University of Waterloo Canada
massive datasets
big data analysis
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Nadine Moacdieh
Carleton University Canada
data overload
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Esther Kang
University of Bristol United Kingdom
information overload
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W. Neuman
New York University United States of America
information overload
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Sampath Bemgal
University of New Brunswick Canada
cognitive emotional overload
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René Wittmer
Université de Montréal Canada
overutilization
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Pankaj Das
University of California, San Diego United States of America
oversampling
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Jun Xie
Purdue University United States of America
massive data
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Michael Zhu
Purdue University United States of America
massive data
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Peregrin Spielholz
University of Washington United States of America
human workload
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Dorine Swinkels
Radboud University Netherlands
iron overload
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