Applications of Data Science to High Throughput Experimentation | AIChE

Applications of Data Science to High Throughput Experimentation

Chair(s)

Nance, E., UNIVERSITY OF WASHINGTON

Co-chair(s)

This session invites submissions on research that aims to leverage tools of data science for high throughput experimental work. Data-driven approaches include, but are not limited to, robotics approaches for automatic experimental work, high-throughput screening, machine learning, data mining, meta-analysis. All research areas of interest to chemical engineers are welcome. Submissions should articulate the impact of data science on the problem of interest and clearly articulate the experimental component of the work.

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Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00