Distributed Estimation Control Professors in Global

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Robert Balog
Texas A&M University United States of America
distributed dc power systems
model predictive control
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Robson De Grande
Brock University Canada
distributed collaborative virtual simulation systems
large scale distributed systems
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Kirsten Morris
University of Waterloo Canada
control & estimation systems
estimator controller design
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Suman Chakravorty
Texas A&M University United States of America
estimation
stochastic control
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Dena Firoozi
University of Toronto Canada
estimation theory
stochastic control
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Hector Budman
University of Waterloo Canada
model predictive control
modeling control
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Maurice Heemels
Eindhoven University of Technology Belgium
model predictive control
networked control
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Eric Kerrigan
Imperial College London United Kingdom
model predictive control
control optimization
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Frederi Viens
Michigan State University United States of America
stochastic control
parameter estimation
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Dinesh Jayaraman
University of Pennsylvania United States of America
estimation
data-driven control algorithms
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Sihao Sun
Delft University of Technology Netherlands
estimation
fault-tolerant control
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Arash Khatamianfar
University of New South Wales Australia
model predictive control
dynamic systems modeling and control
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Ya‑jun Pan
Dalhousie University Canada
distributed control networks
model predictive control
networked control systems
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Philip Paré
Purdue University United States of America
data-informed control methods
parameter estimation
control of dynamic networked systems
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Malcolm Low
Singapore Institute of Technology Singapore
discrete event simulation
parallel distributed computing
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Alessandro Saccon
Eindhoven University of Technology Belgium
estimation
numerical optimal control
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Subhrakanti Dey
Uppsala University Sweden
distributed optimization
distributed machine learning
estimation
networked control systems
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Venkata Dinavahi
University of Alberta Canada
parallel distributed computing
digital control
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Joseph Moore
Johns Hopkins University United States of America
computational control
learning-based control
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Yuhang Deng
Linköping University Sweden
distributed optimization
decentralized machine learning
consensus in distributed systems
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Mark Cannon
University of Oxford United Kingdom
stochastic model predictive control
control optimization
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