01/22/20 - 12:00 PM to 2:00 PM
MN ACS: Professor Jason Goodpaster
Machine Learning in Quantum Chemistry
6:00 p.m. - Dinner
7:00 p.m. - Speaker
Kate and Michael Barany Conference Room (117/119 Smith Hall) for dinner and 331 Smith Hall for speaker
Please sign up by Monday, Jan. 20
$15 for dinner
$5 (students) for dinner
No cost to attend the seminar
Buffet dinner provided by Holy Land Catering
Machine Learning and data science is poised to revolutionize chemical research. As the field of machine learning has expanded, a variety of methodologies have become commonplace, such as kernel ridge regression, Gaussian process regression, and neural networks. In this talk, I will outline the basics of machine learning, the basics of these methodologies, and when these methodologies can and should be applied. Additionally, I will discuss the work my research group has been doing in applying these methodologies to quantum chemistry.
Jason Goodpaster is an assistant professor of chemistry and chemical physics at the University of Minnesota. His research focuses on the development of new quantum chemistry methods and applying these methods to a wide variety of chemical systems including: metal organic frameworks, inorganic catalysis, surface enhanced ramen spectroscopy, and electrochemistry. Goodpaster obtained his doctorate at Caltech and performed his postdoctoral work at Lawrence Berkeley National Lab.