Advances in Machine Learning and Intelligent Systems

Chair(s):
Boukouvala, F., Georgia Institute of Technology
Co-chair(s):
Realff, M. J., Georgia Institute of Technology

Data-driven approaches are playing an increasingly significant role in chemical engineering. This session solicits submissions pertaining to both methodological advances in machine learning as well as application-driven case studies demonstrating the use large data sets and machine learning to infer correlations, develop models, as well as to improve processes/systems through data-driven optimization and control. Particular emphasis will be given to applications which employ an adaptive data-driven approach, through which data-mining and machine learning are used to create intelligent systems, which adaptively learn from the data.

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Individuals

AIChE Members $150.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
Non-Members $225.00