Statistical Anomaly Detection Professors in Global

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Chris Holmes
University of Oxford United Kingdom
spatial statistics
statistical genomics
pattern recognition
statistical genetics
stochastic simulation
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Leman Akoglu
Carnegie Mellon University United States of America
anomaly detection
outlier detection
pattern discovery
machine learning
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Christian Maack
Aalborg University Denmark
anomaly detection
stochastic modelling
machine learning
fault detection
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Nazim Khan
University of Western Australia Australia
statistical model selection
statistical computing
stochastic modelling
statistical clustering
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Hina Shaheen
University of Manitoba Canada
statistical machine learning
machine learning
computational modelling
data analysis
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Hao Zhang
Purdue University United States of America
statistical computing
spatial statistics
machine learning
spatial analysis
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Da Zhao
University of Melbourne Australia
statistical modeling
machine learning
predictive modeling
data analysis
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James Norris
University of Cambridge United Kingdom
statistical modeling
statistical theory
mathematical statistics
data analysis
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Xiaoqing Wang
Texas A&M University United States of America
statistical modeling
statistical methods
machine learning
data analysis
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A.c.c. Coolen
Radboud University Netherlands
statistical inference
machine learning
predictive analysis
random networks
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Rajesh Ranganath
New York University United States of America
statistical inference
out-of-distribution detection
machine learning
probabilistic inference
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Andrey Feuerverger
University of Toronto Canada
statistical theory
statistical inverse problems
machine learning
mathematical statistics
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Mehdi Moradi
Umeå University Sweden
statistical learning
spatial statistics
change-point detection
mathematical statistics
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Chinh Lee
Monash University Australia
statistical quality control
machine learning
predictive modeling
statistical business analytics
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Alfred Hero
University of Michigan United States of America
anomaly detection
statistical machine learning
data analysis
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Paula Branco
University of Ottawa Canada
anomaly detection
machine learning
predictive analytics
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Sankaran Iyer
University of New South Wales Australia
anomaly detection
object detection
pedestrian detection
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Anindya Das
Umeå University Sweden
anomaly detection
machine learning
adaptive deviation learning
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Barbara Frommann
University of Bonn Germany
statistical analysis
statistical inference
scientific machine learning
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Jethro Linley
University of Glasgow United Kingdom
statistical machine learning
statistical modelling
predictive analytics
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Kim Blackmore
Australian National University Australia
anomalous change detection
pattern recognition
machine learning
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