Machine Learning in Chemical Sciences
Required Availability
Spring 2022Course Credit?
Yes - CHE 491Paid Position?
NoFaculty
Tibor SzilvasiDescription
We are interested in predicting the macroscopic properties of chemical compounds based on their chemical structure and molecular properties using advanced machine learning models. Students are expected to learn data analysis techniques based on support vector machine, decision tree, and neural networks as well as build database on which these analyses will be done. No previous knowledge of machine learning techniques is needed. Matlab knowledge is an advantage.
Special Directions
If interested, please send an email with CWID.