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Extensions of Dynamic Programming, Machine Learning, Discrete Optimization
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Extensions of Dynamic Programming, Machine Learning, Discrete Optimization
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applied mathematics
Peter Schmid
Professor,
Mechanical Engineering
applied mathematics
computational methods
Signal processing
MATLAB
Professor Schmid's research interests are in theoretical and computational fluid dynamics, with emphasis on hydrodynamic stability theory, flow control, model reduction and system identification. He is also interested in computational techniques for flow optimization and quantitative flow analysis.